This document provides an overview of oncology and cancer clinical trials from a data standards and programming perspective. It begins with basic cancer definitions and epidemiology. Key aspects of clinical trials in oncology are then discussed, including complex efficacy endpoints, safety evaluations, and exposure assessments. Standardization efforts through CDISC are summarized, including SDTM and ADaM domains for oncology. Regulatory guidelines from the FDA and EMA are also covered. Throughout, challenges specific to oncology trials from a data and programming standpoint are highlighted. The aim of the PhUSE oncology wiki is also introduced as a resource for further information.
The presentation is intended for Clinical Trial programmers or statisticians who are working on the solid tumor studies in oncology. There are three types of studies in oncology: Solid Tumor, Lymphoma and Leukemia. The solid tumor study usually follow RECIST (Response Evaluation Criteria in Solid Tumor) while Lymphoma follows Cheson and Leukemia follows study-specific criteria. The presentation will provide the brief introduction of RECIST 1.1 such as lesions (target, non target and new) and their selection criteria (size, number and etc). It will also discuss how the changes in tumor measurements will lead to responses (Complete Response, Partial Response, Stable Disease, Progression Disease and Not Evaluable).
Then, the presentation will introduce how RECIST 1.1 data are streamlined in CDISC – mainly in SDTM and ADaM. The presentation will introduce the new oncology SDTM domains - TU (Tumor Identification), TR (Tumor Results) and RS (Response) according to RECIST 1.1. The presentation will also show how ADaM datasets can be created for the tumor response evaluation and analysis in ORR (Objective Response Rate), PFS (Progression Free Survival) and TTP (Time to Progression).
Two different use cases to obtain best response using recist 11 sdtm and a ...Kevin Lee
Each therapeutic area has its own unique data collection and analysis. Especially, Oncology has a unique way to collect and analyze the data and one of unique data points in oncology study is best response. The paper will be based on Solid Tumor and RECIST 1.1, and it will show use cases on how best response will be collected in SDTM domains and derived in ADaM datasets using RECIST 1.1 in solid tumor oncology study.
The paper will provide the brief introduction of RECIST 1.1 such as legions type (i.e., target, non-target and new) and their selection criteria(e.g., size and number). The paper will provide the practical application on how tumor measurements for target and non-target lesions are collected in TR domain, how those measurement are assessed according to RECIST 1.1, and eventually how responses are represented in RS domain based on the assessment from tumor measurements.
We will also put in prospective a pictorial road map on which way we choose to derive responses to give a prospective to the user and the process to get from beginning to end objective. This paper will also discuss a use case where the visit level response are been derived programmatically in ADaM and perform a sensitive analysis in comparison to investigator provides visit level response to SDTM RS domain. This case study will help user identify the differences between both the methodologies and help answer any anomalies from investigator inference prospective vs analytical calculations by the programmer.
New response evaluation criteria in solid tumours Ameen Rageh
RECIST provides standardized criteria for evaluating tumor response to treatment in clinical trials. It defines criteria for complete response, partial response, stable disease, and progressive disease based on tumor measurements. Tumors must be accurately measured at baseline using CT or MRI. Target lesions are up to 5 measurable lesions selected for their ability to be reproducibly measured. Non-target lesions including small lesions and lymph nodes are also recorded. Tumor measurements are compared between scans to determine the patient's response according to RECIST criteria. The appearance of new lesions indicates disease progression.
Presented at PhUSE 2013
The evaluation of efficacy in oncology studies, in particular for solid tumors, is pretty standard and well defined by several regulatory guidance (e.g. EMA and FDA), including some specific cancer type guidance (e.g. NSCLC from FDA).
Although some references will be also given for non-solid tumors, the paper will mainly focus on solid tumors efficacy
endpoints.
Overall Survival, Best Overall Response as per RECIST criteria, Progression Free Survival (PFS), Time to Progression (TTP), Best Overall Response Rate are some of the key efficacy indicators that will be discussed.
Audio and slides for this presentation are available on YouTube: http://youtu.be/NzJ_fvSxwGk
Sara Tolaney, MD, MPH, a breast oncologist with the Susan F. Smith Center for Women's Cancers at Dana-Farber Cancer Institute, gives an overview of phase I clinical trials and some of the new drugs being tested to treat breast cancer. This talk was originally given at the Metastatic Breast Cancer Forum at Dana-Farber on Oct. 5, 2013.
This document discusses CDISC standards for representing survival data from oncology clinical trials. It provides an overview of CDISC and describes the SDTM and ADaM domains that are useful for capturing efficacy endpoints involving survival, such as overall survival, progression-free survival and tumor response. Examples are given of how survival data from different patients would be represented in an ADTTE (Analysis Dataset for Time to Event) dataset according to CDISC ADaM standards.
This document summarizes key efficacy endpoints used in oncology clinical trials, including for solid tumors and non-solid tumors like acute myeloid leukemia. For solid tumors, the best overall response (BOR) is assessed using RECIST criteria to evaluate tumor shrinkage or progression based on target and non-target lesion measurements. Key time-to-event endpoints discussed include overall survival (OS), progression-free survival (PFS), and time to progression (TTP). For acute myeloid leukemia, response is assessed based on blood counts and bone marrow blast percentage according to International Working Group criteria, with endpoints like complete remission rate and event-free survival. Surrogate endpoints are also discussed.
This document provides an overview of oncology and cancer clinical trials from a data standards and programming perspective. It begins with basic cancer definitions and epidemiology. Key aspects of clinical trials in oncology are then discussed, including complex efficacy endpoints, safety evaluations, and exposure assessments. Standardization efforts through CDISC are summarized, including SDTM and ADaM domains for oncology. Regulatory guidelines from the FDA and EMA are also covered. Throughout, challenges specific to oncology trials from a data and programming standpoint are highlighted. The aim of the PhUSE oncology wiki is also introduced as a resource for further information.
The presentation is intended for Clinical Trial programmers or statisticians who are working on the solid tumor studies in oncology. There are three types of studies in oncology: Solid Tumor, Lymphoma and Leukemia. The solid tumor study usually follow RECIST (Response Evaluation Criteria in Solid Tumor) while Lymphoma follows Cheson and Leukemia follows study-specific criteria. The presentation will provide the brief introduction of RECIST 1.1 such as lesions (target, non target and new) and their selection criteria (size, number and etc). It will also discuss how the changes in tumor measurements will lead to responses (Complete Response, Partial Response, Stable Disease, Progression Disease and Not Evaluable).
Then, the presentation will introduce how RECIST 1.1 data are streamlined in CDISC – mainly in SDTM and ADaM. The presentation will introduce the new oncology SDTM domains - TU (Tumor Identification), TR (Tumor Results) and RS (Response) according to RECIST 1.1. The presentation will also show how ADaM datasets can be created for the tumor response evaluation and analysis in ORR (Objective Response Rate), PFS (Progression Free Survival) and TTP (Time to Progression).
Two different use cases to obtain best response using recist 11 sdtm and a ...Kevin Lee
Each therapeutic area has its own unique data collection and analysis. Especially, Oncology has a unique way to collect and analyze the data and one of unique data points in oncology study is best response. The paper will be based on Solid Tumor and RECIST 1.1, and it will show use cases on how best response will be collected in SDTM domains and derived in ADaM datasets using RECIST 1.1 in solid tumor oncology study.
The paper will provide the brief introduction of RECIST 1.1 such as legions type (i.e., target, non-target and new) and their selection criteria(e.g., size and number). The paper will provide the practical application on how tumor measurements for target and non-target lesions are collected in TR domain, how those measurement are assessed according to RECIST 1.1, and eventually how responses are represented in RS domain based on the assessment from tumor measurements.
We will also put in prospective a pictorial road map on which way we choose to derive responses to give a prospective to the user and the process to get from beginning to end objective. This paper will also discuss a use case where the visit level response are been derived programmatically in ADaM and perform a sensitive analysis in comparison to investigator provides visit level response to SDTM RS domain. This case study will help user identify the differences between both the methodologies and help answer any anomalies from investigator inference prospective vs analytical calculations by the programmer.
New response evaluation criteria in solid tumours Ameen Rageh
RECIST provides standardized criteria for evaluating tumor response to treatment in clinical trials. It defines criteria for complete response, partial response, stable disease, and progressive disease based on tumor measurements. Tumors must be accurately measured at baseline using CT or MRI. Target lesions are up to 5 measurable lesions selected for their ability to be reproducibly measured. Non-target lesions including small lesions and lymph nodes are also recorded. Tumor measurements are compared between scans to determine the patient's response according to RECIST criteria. The appearance of new lesions indicates disease progression.
Presented at PhUSE 2013
The evaluation of efficacy in oncology studies, in particular for solid tumors, is pretty standard and well defined by several regulatory guidance (e.g. EMA and FDA), including some specific cancer type guidance (e.g. NSCLC from FDA).
Although some references will be also given for non-solid tumors, the paper will mainly focus on solid tumors efficacy
endpoints.
Overall Survival, Best Overall Response as per RECIST criteria, Progression Free Survival (PFS), Time to Progression (TTP), Best Overall Response Rate are some of the key efficacy indicators that will be discussed.
Audio and slides for this presentation are available on YouTube: http://youtu.be/NzJ_fvSxwGk
Sara Tolaney, MD, MPH, a breast oncologist with the Susan F. Smith Center for Women's Cancers at Dana-Farber Cancer Institute, gives an overview of phase I clinical trials and some of the new drugs being tested to treat breast cancer. This talk was originally given at the Metastatic Breast Cancer Forum at Dana-Farber on Oct. 5, 2013.
This document discusses CDISC standards for representing survival data from oncology clinical trials. It provides an overview of CDISC and describes the SDTM and ADaM domains that are useful for capturing efficacy endpoints involving survival, such as overall survival, progression-free survival and tumor response. Examples are given of how survival data from different patients would be represented in an ADTTE (Analysis Dataset for Time to Event) dataset according to CDISC ADaM standards.
This document summarizes key efficacy endpoints used in oncology clinical trials, including for solid tumors and non-solid tumors like acute myeloid leukemia. For solid tumors, the best overall response (BOR) is assessed using RECIST criteria to evaluate tumor shrinkage or progression based on target and non-target lesion measurements. Key time-to-event endpoints discussed include overall survival (OS), progression-free survival (PFS), and time to progression (TTP). For acute myeloid leukemia, response is assessed based on blood counts and bone marrow blast percentage according to International Working Group criteria, with endpoints like complete remission rate and event-free survival. Surrogate endpoints are also discussed.
The presentation is intended for Clinical Trial programmers or statisticians who are working on the oncology lymphoma clinical trial studies. There are three types of studies in oncology: Solid Tumor, Lymphoma and Leukemia. The lymphoma studies usually follow Cheson while solid tumor follow RECIST (Response Evaluation Criteria in Solid Tumor) and Leukemia studies follow IWCLL(Internal Working Group on Chronic Lymphocytic Leukemia). There are two version of Cheson – 1999 and 2007. The presentation will be based on Cheson 2007.
The presentation will provide the brief introduction of Cheson 2007 such as legions (enlarged lymph node, nodal masses and extra nodal masses) and their types (target, non target and new) . The lymphoma studies need to collect the measurements of lesions (the longest diameter, its greatest transverse diameter and the sum of diameters), PET scan on those lesions, Bone Marrow assessment, Spleen and Liver assessment. Cheson 2007 explains how each assessment is made to determine responses (Complete Response, Partial Response, Stable Disease and Progression Disease).
Then, the paper will show how tumor data are streamlined in CDISC – mainly in SDTM and ADaM. The paper will introduce the new oncology SDTM domains - TU (Tumor Identification), TR (Tumor Results) and RS (Response) and oncology ADaM dataset – Time to Event (--TTE). The paper will show how Cheson 2007 data points are collected in SDTM domain - tumor measurements in TR and TU, PET scan in TR and TU, Bone Marrow in LB and FA, Spleen and Liver assessments in PE and response in RS. The paper will also show how ADaM time to event datasets can be used for oncology analysis such as OR(Overall Survival) and PFS (Progression Free Survival).
The RECIST guidelines provide standardized criteria for evaluating tumor response in cancer clinical trials. They were developed in 2000 by an international working group to simplify and standardize previous WHO response criteria. Key aspects of the RECIST guidelines include defining measurable and non-measurable lesions, criteria for complete response, partial response, stable disease and progressive disease based on tumor size measurements, and recommendations for frequency of tumor re-evaluation and confirming responses. The guidelines aim to facilitate objective and reproducible assessments of tumor burden and treatment response.
This document summarizes different adaptive designs that can be used in early phase oncology trials. It discusses modifications that can be made to dose levels, tumor types considered, and early termination of selected arms. Specific adaptive designs covered include model-based dose escalation methods like the N-CRM and mTPI, zone-based designs for combination treatments, methods for stopping early in single-arm trials, basket and umbrella trial designs, and an example of the Keytruda first-time-in-human study. The goal of adaptive designs is to incorporate interim data to modify trial aspects and make trials more efficient.
The document summarizes key points from a presentation given by Dr. Bhaswat S. Chakraborty at the National Conference on Innovation in Pharmaceutical Industry on clinical development of new drugs. It discusses various endpoints that can be considered in cancer clinical trials, including overall survival, progression-free survival, tumor response rates, quality of life measures, biomarkers, and symptom-based endpoints. It notes the merits and limitations of different endpoints and trial designs.
1) RECIST (Response Evaluation Criteria in Solid Tumors) provides a standardized method for measuring tumor response to therapy using anatomical imaging. It assesses target lesions that are measured one-dimensionally and non-target lesions that are evaluated qualitatively.
2) RECIST is primarily intended for use in clinical trials where tumor response is the main endpoint. It simplifies prior criteria while updating for new imaging technologies. RECIST 1.1 is the current version published in 2009.
3) According to RECIST, tumor responses are classified as complete response, partial response, stable disease, or progressive disease based on a percentage change in the sum of diameters of target lesions from baseline. This provides a reproducible method for
Interim Analysis of Clinical Trial Data: Implementation and Practical AdviceNAMSA
This document discusses interim analyses of clinical trial data. It describes different types of interim analyses including early stopping for safety or efficacy, sample size re-assessments, and administrative analyses. Early stopping for safety is generally done by a data monitoring committee to ensure participant safety. Early stopping for efficacy can determine whether a trial meets success criteria or shows futility. Sample size can be re-estimated based on nuisance parameters or treatment effects. Interim analyses are most useful when the alternative hypothesis is uncertain, enrollment is slow, or endpoints are acute. The document recommends doing some form of interim analysis or monitoring in almost all cases.
The document provides guidelines for assessing response to treatment for malignant lymphoma. It defines measurable and non-measurable lesions, how to choose target lesions, and how to determine response based on changes in target and non-target lesions, new lesions, and overall response combining radiographic and clinical data. Response is categorized as complete remission, partial remission, stable disease, progressive disease, or unable to evaluate based on specific criteria for changes in lesions.
This document discusses multicentric clinical trials. It begins by defining clinical trials and introducing that a multicenter trial is conducted across multiple medical centers. Key points are that multicenter trials require standardization of procedures, uniformity, high data quality, and collaboration across sites. The document distinguishes between multi-site and multicentric studies, noting that in multicentric studies investigators at sites are co-investigators in planning and responsible for results, while in multi-site studies sites merely carry out tasks. Coordination in multicenter studies involves centralized activities like protocol development and data management to standardize procedures. Advantages include larger sample sizes and evaluating efficacy across populations. The document concludes by summarizing a phase II multicenter trial of sunit
This document provides an overview of clinical trials and their various phases. It discusses how clinical trials are used to test potential interventions in humans to determine if they should be adopted for general use. The different phases of clinical trials are described, including phase I-IV. Key aspects of clinical trial design such as randomization, blinding, and placebos are explained. Hypothesis testing and its role in statistical analysis is also summarized.
This document discusses the phases of clinical trials. It begins by defining a clinical trial and explaining their importance. It then outlines the typical phases:
Phase I trials involve small groups of healthy volunteers and focus on safety, tolerability and pharmacokinetics. Phase II trials enroll larger numbers of patients to study efficacy and further evaluate safety. Phase III trials involve thousands of patients and aim to confirm efficacy and further monitor safety. Phase IV trials occur after marketing approval to further monitor long-term safety and efficacy.
The document provides details on the objectives, features, sample sizes, and information gained from each phase of trials. It discusses microdosing studies, pharmacogenomics studies, and post-marketing surveillance. In summary
- RECIST provides standardized criteria for evaluating tumor response to treatment in clinical trials. It defines measurable lesions and how they are assessed, including complete response, partial response and disease progression based on tumor size changes.
- Key changes from WHO to RECIST included using the longest diameter of lesions rather than bidimensional measurements, limiting the number of target lesions assessed, and defining minimum lesion sizes.
- RECIST 1.1 further clarified disease progression definitions and included FDG-PET in detecting new lesions. Standardizing response criteria allows more consistent evaluation of cancer treatments across clinical trials.
This document provides an overview of clinical trials and statistics. It discusses key concepts like randomized controlled trials, bias, standard deviation, p-values, confidence intervals, risk, odds ratios, and numbers needed to treat. The objectives are to help understand how to interpret clinical trial results and appreciate statistically significant versus clinically meaningful differences. Understanding basic statistics is important for critically evaluating the medical literature and making evidence-based clinical decisions.
The document discusses several Trial Design domains from CDISC, including Trial Arms (TA), Trial Elements (TE), and Trial Visits (TS). It describes the key variables in each domain like ARMCD, ETCD, ELEMENT, EPOCH, VISITNUM, and start/end rules for trial elements and visits. The domains are used to represent the overall study design and plan without subject-level data.
Explaining the importance of a database lock in clinical researchTrialJoin
One of the most crucial aspects of research is clinical data management or CDM. Proper CDM will generate results with excellent quality, integrity, and reliability. Quality data is essential in order to support the final conclusions of a certain study.
The person responsible for this area of research is called a clinical data manager. This job position can be filled by a PI, a study coordinator, or a CRA. No matter who fills this position at your site, data management has to be done promptly and correctly in order to generate the best results. Aside from all the other reasons why data management is so important, it’s also what determines the future IP (investigational product) development.
Immunotherapy maintenence for advanced urothelial cancerChandan K Das
- JAVELIN Bladder 100 was a phase 3 trial investigating avelumab maintenance therapy after platinum-based chemotherapy in patients with advanced urothelial carcinoma.
- The trial found avelumab maintenance significantly improved overall survival compared to best supportive care alone, with a 31% reduction in risk of death. Progression-free survival was also significantly improved.
- Subgroup analyses found overall survival benefits were consistent across all patient subgroups, including those with PD-L1-negative tumors. Response rates were also higher with avelumab maintenance.
- The safety profile of avelumab was manageable, with most treatment-related adverse events being grade 1-2 in severity and no new safety signals
The document discusses stage III non-small cell lung cancer (NSCLC), noting its heterogeneity in presentation, risk factors, and treatment approaches. Stage III NSCLC encompasses locally advanced tumors with varying degrees of lymph node involvement. Effective treatment requires a multidisciplinary team and individualized treatment plans based on tumor characteristics and patient health. While surgery can potentially cure some stage III NSCLC, many patients require pre-operative or post-operative chemotherapy and radiation therapy to improve outcomes.
Chapter 25 assessment of clincal responsesNilesh Kucha
The document discusses guidelines for assessing clinical response in cancer patients based on tumor size changes. The RECIST (Response Evaluation Criteria in Solid Tumors) criteria provide a standardized approach for measuring lesions and determining objective tumor responses. Key points include defining measurable vs. non-measurable lesions, methods for measurement and assessment, and criteria for complete response, partial response, stable disease and progressive disease based on tumor burden changes. The guidelines aim to improve consistency in evaluating clinical trial outcomes.
CDISC journey in solid tumor using recist 1.1 (Paper)Kevin Lee
This document summarizes the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 guidelines for evaluating tumor response in clinical trials. It introduces the three types of oncology studies, defines target and non-target lesions, and describes how lesion measurements are used to determine complete response, partial response, stable disease, progression disease, and not evaluable responses. It also discusses how RECIST 1.1 data are organized in CDISC SDTM and ADaM domains, and provides an example of how these domains can be used to evaluate tumor response and analyze outcomes like objective response rate, progression-free survival, and time to progression.
The presentation is intended for Clinical Trial programmers or statisticians who are working on the oncology lymphoma clinical trial studies. There are three types of studies in oncology: Solid Tumor, Lymphoma and Leukemia. The lymphoma studies usually follow Cheson while solid tumor follow RECIST (Response Evaluation Criteria in Solid Tumor) and Leukemia studies follow IWCLL(Internal Working Group on Chronic Lymphocytic Leukemia). There are two version of Cheson – 1999 and 2007. The presentation will be based on Cheson 2007.
The presentation will provide the brief introduction of Cheson 2007 such as legions (enlarged lymph node, nodal masses and extra nodal masses) and their types (target, non target and new) . The lymphoma studies need to collect the measurements of lesions (the longest diameter, its greatest transverse diameter and the sum of diameters), PET scan on those lesions, Bone Marrow assessment, Spleen and Liver assessment. Cheson 2007 explains how each assessment is made to determine responses (Complete Response, Partial Response, Stable Disease and Progression Disease).
Then, the paper will show how tumor data are streamlined in CDISC – mainly in SDTM and ADaM. The paper will introduce the new oncology SDTM domains - TU (Tumor Identification), TR (Tumor Results) and RS (Response) and oncology ADaM dataset – Time to Event (--TTE). The paper will show how Cheson 2007 data points are collected in SDTM domain - tumor measurements in TR and TU, PET scan in TR and TU, Bone Marrow in LB and FA, Spleen and Liver assessments in PE and response in RS. The paper will also show how ADaM time to event datasets can be used for oncology analysis such as OR(Overall Survival) and PFS (Progression Free Survival).
The RECIST guidelines provide standardized criteria for evaluating tumor response in cancer clinical trials. They were developed in 2000 by an international working group to simplify and standardize previous WHO response criteria. Key aspects of the RECIST guidelines include defining measurable and non-measurable lesions, criteria for complete response, partial response, stable disease and progressive disease based on tumor size measurements, and recommendations for frequency of tumor re-evaluation and confirming responses. The guidelines aim to facilitate objective and reproducible assessments of tumor burden and treatment response.
This document summarizes different adaptive designs that can be used in early phase oncology trials. It discusses modifications that can be made to dose levels, tumor types considered, and early termination of selected arms. Specific adaptive designs covered include model-based dose escalation methods like the N-CRM and mTPI, zone-based designs for combination treatments, methods for stopping early in single-arm trials, basket and umbrella trial designs, and an example of the Keytruda first-time-in-human study. The goal of adaptive designs is to incorporate interim data to modify trial aspects and make trials more efficient.
The document summarizes key points from a presentation given by Dr. Bhaswat S. Chakraborty at the National Conference on Innovation in Pharmaceutical Industry on clinical development of new drugs. It discusses various endpoints that can be considered in cancer clinical trials, including overall survival, progression-free survival, tumor response rates, quality of life measures, biomarkers, and symptom-based endpoints. It notes the merits and limitations of different endpoints and trial designs.
1) RECIST (Response Evaluation Criteria in Solid Tumors) provides a standardized method for measuring tumor response to therapy using anatomical imaging. It assesses target lesions that are measured one-dimensionally and non-target lesions that are evaluated qualitatively.
2) RECIST is primarily intended for use in clinical trials where tumor response is the main endpoint. It simplifies prior criteria while updating for new imaging technologies. RECIST 1.1 is the current version published in 2009.
3) According to RECIST, tumor responses are classified as complete response, partial response, stable disease, or progressive disease based on a percentage change in the sum of diameters of target lesions from baseline. This provides a reproducible method for
Interim Analysis of Clinical Trial Data: Implementation and Practical AdviceNAMSA
This document discusses interim analyses of clinical trial data. It describes different types of interim analyses including early stopping for safety or efficacy, sample size re-assessments, and administrative analyses. Early stopping for safety is generally done by a data monitoring committee to ensure participant safety. Early stopping for efficacy can determine whether a trial meets success criteria or shows futility. Sample size can be re-estimated based on nuisance parameters or treatment effects. Interim analyses are most useful when the alternative hypothesis is uncertain, enrollment is slow, or endpoints are acute. The document recommends doing some form of interim analysis or monitoring in almost all cases.
The document provides guidelines for assessing response to treatment for malignant lymphoma. It defines measurable and non-measurable lesions, how to choose target lesions, and how to determine response based on changes in target and non-target lesions, new lesions, and overall response combining radiographic and clinical data. Response is categorized as complete remission, partial remission, stable disease, progressive disease, or unable to evaluate based on specific criteria for changes in lesions.
This document discusses multicentric clinical trials. It begins by defining clinical trials and introducing that a multicenter trial is conducted across multiple medical centers. Key points are that multicenter trials require standardization of procedures, uniformity, high data quality, and collaboration across sites. The document distinguishes between multi-site and multicentric studies, noting that in multicentric studies investigators at sites are co-investigators in planning and responsible for results, while in multi-site studies sites merely carry out tasks. Coordination in multicenter studies involves centralized activities like protocol development and data management to standardize procedures. Advantages include larger sample sizes and evaluating efficacy across populations. The document concludes by summarizing a phase II multicenter trial of sunit
This document provides an overview of clinical trials and their various phases. It discusses how clinical trials are used to test potential interventions in humans to determine if they should be adopted for general use. The different phases of clinical trials are described, including phase I-IV. Key aspects of clinical trial design such as randomization, blinding, and placebos are explained. Hypothesis testing and its role in statistical analysis is also summarized.
This document discusses the phases of clinical trials. It begins by defining a clinical trial and explaining their importance. It then outlines the typical phases:
Phase I trials involve small groups of healthy volunteers and focus on safety, tolerability and pharmacokinetics. Phase II trials enroll larger numbers of patients to study efficacy and further evaluate safety. Phase III trials involve thousands of patients and aim to confirm efficacy and further monitor safety. Phase IV trials occur after marketing approval to further monitor long-term safety and efficacy.
The document provides details on the objectives, features, sample sizes, and information gained from each phase of trials. It discusses microdosing studies, pharmacogenomics studies, and post-marketing surveillance. In summary
- RECIST provides standardized criteria for evaluating tumor response to treatment in clinical trials. It defines measurable lesions and how they are assessed, including complete response, partial response and disease progression based on tumor size changes.
- Key changes from WHO to RECIST included using the longest diameter of lesions rather than bidimensional measurements, limiting the number of target lesions assessed, and defining minimum lesion sizes.
- RECIST 1.1 further clarified disease progression definitions and included FDG-PET in detecting new lesions. Standardizing response criteria allows more consistent evaluation of cancer treatments across clinical trials.
This document provides an overview of clinical trials and statistics. It discusses key concepts like randomized controlled trials, bias, standard deviation, p-values, confidence intervals, risk, odds ratios, and numbers needed to treat. The objectives are to help understand how to interpret clinical trial results and appreciate statistically significant versus clinically meaningful differences. Understanding basic statistics is important for critically evaluating the medical literature and making evidence-based clinical decisions.
The document discusses several Trial Design domains from CDISC, including Trial Arms (TA), Trial Elements (TE), and Trial Visits (TS). It describes the key variables in each domain like ARMCD, ETCD, ELEMENT, EPOCH, VISITNUM, and start/end rules for trial elements and visits. The domains are used to represent the overall study design and plan without subject-level data.
Explaining the importance of a database lock in clinical researchTrialJoin
One of the most crucial aspects of research is clinical data management or CDM. Proper CDM will generate results with excellent quality, integrity, and reliability. Quality data is essential in order to support the final conclusions of a certain study.
The person responsible for this area of research is called a clinical data manager. This job position can be filled by a PI, a study coordinator, or a CRA. No matter who fills this position at your site, data management has to be done promptly and correctly in order to generate the best results. Aside from all the other reasons why data management is so important, it’s also what determines the future IP (investigational product) development.
Immunotherapy maintenence for advanced urothelial cancerChandan K Das
- JAVELIN Bladder 100 was a phase 3 trial investigating avelumab maintenance therapy after platinum-based chemotherapy in patients with advanced urothelial carcinoma.
- The trial found avelumab maintenance significantly improved overall survival compared to best supportive care alone, with a 31% reduction in risk of death. Progression-free survival was also significantly improved.
- Subgroup analyses found overall survival benefits were consistent across all patient subgroups, including those with PD-L1-negative tumors. Response rates were also higher with avelumab maintenance.
- The safety profile of avelumab was manageable, with most treatment-related adverse events being grade 1-2 in severity and no new safety signals
The document discusses stage III non-small cell lung cancer (NSCLC), noting its heterogeneity in presentation, risk factors, and treatment approaches. Stage III NSCLC encompasses locally advanced tumors with varying degrees of lymph node involvement. Effective treatment requires a multidisciplinary team and individualized treatment plans based on tumor characteristics and patient health. While surgery can potentially cure some stage III NSCLC, many patients require pre-operative or post-operative chemotherapy and radiation therapy to improve outcomes.
Chapter 25 assessment of clincal responsesNilesh Kucha
The document discusses guidelines for assessing clinical response in cancer patients based on tumor size changes. The RECIST (Response Evaluation Criteria in Solid Tumors) criteria provide a standardized approach for measuring lesions and determining objective tumor responses. Key points include defining measurable vs. non-measurable lesions, methods for measurement and assessment, and criteria for complete response, partial response, stable disease and progressive disease based on tumor burden changes. The guidelines aim to improve consistency in evaluating clinical trial outcomes.
CDISC journey in solid tumor using recist 1.1 (Paper)Kevin Lee
This document summarizes the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 guidelines for evaluating tumor response in clinical trials. It introduces the three types of oncology studies, defines target and non-target lesions, and describes how lesion measurements are used to determine complete response, partial response, stable disease, progression disease, and not evaluable responses. It also discusses how RECIST 1.1 data are organized in CDISC SDTM and ADaM domains, and provides an example of how these domains can be used to evaluate tumor response and analyze outcomes like objective response rate, progression-free survival, and time to progression.
This document discusses the evolution of criteria used to evaluate tumor response to cancer treatment. It describes early attempts in the 1960s and outlines key criteria developed by the WHO in the late 1970s and early 1980s. It then summarizes the RECIST criteria developed in 2000 which standardized tumor response evaluation using unidimensional measurements. RECIST 1.1 further revised criteria in 2009. Overall it provides a history of response evaluation criteria and compares features of WHO, RECIST 1.0 and RECIST 1.1.
This document discusses efficacy endpoints in oncology drug development. It begins with an introduction to endpoints used in early and late phase trials. Overall survival is discussed as the gold standard, but surrogate endpoints are also examined, including objective response rate, progression-free survival, and time to progression. Considerations for various surrogate endpoints like bias, validation, and data management are provided. The document reviews regulatory requirements and considerations for different cancer types and endpoints.
The document provides an introduction to clinical trials for cancer drug development. It discusses moving potential new therapies from preclinical testing in animal models through the different phases of clinical trials in humans. Phase I trials determine safety and dosing, phase II screens for anti-tumor activity, and phase III tests for efficacy in larger patient populations through randomized controlled trials. Ethical review and informed consent are required throughout the clinical trial process to protect patient safety and rights.
This document summarizes an introduction to clinical trials presented by Jan B. Vermorken. It outlines the process of moving new cancer therapies from the laboratory to clinical trials, including preclinical testing requirements, phases of clinical trials (I-III), response criteria, and considerations for trials of non-cytotoxic agents. It also discusses the roles and functions of ethics committees in overseeing clinical trials to protect participants.
Ct lecture 8. comparing two groups categorical dataHau Pham
A workshop on analysis of clinical studies was held at Can Tho University of Medicine and Pharmacy in April 2012. The workshop covered topics such as comparing groups using categorical data, metrics to measure treatment effect such as difference, relative risk, odds ratio, and number needed to treat. Examples of randomized controlled trials, case-control studies, and cohort studies were presented to illustrate the appropriate effect measures and statistical tests for different study designs. R software was introduced to demonstrate how to calculate confidence intervals for differences, relative risks, and odds ratios.
Surrogate Endpoints: Are drug review processes flexible enough to expedite pa...CanCertainty
This document discusses the use of surrogate endpoints in cancer clinical trials as an alternative to overall survival. It provides background on what constitutes a valid surrogate endpoint and examples of endpoints that are not good surrogates. The document notes that validation of surrogate endpoints is often lacking, especially for early-stage cancers. An analysis of clinical trials found that the majority of trials for early-stage solid tumors use surrogate endpoints rather than traditional endpoints like overall survival. This increasing reliance on surrogate endpoints may impact regulatory reviews and reimbursement decisions in the future.
While T4 stage, fewer than 12 lymph nodes, and absence of MMR-D are factors considered in deciding adjuvant chemotherapy for Stage II CRC, they are not definitive standards. Currently, there are no established molecular markers that clearly identify patients with high or low risk of recurrence or benefit from chemotherapy for Stage II colon cancer. Researchers are working to develop improved algorithms incorporating clinical, pathological, and emerging molecular markers to better guide treatment decisions.
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Everywhere in Europe the survival rate of cancer has improved. As of today, there are around 10 million European cancer survivors of which more than a third are of working age. Although not being a death sentence anymore, cancer risks to remain a life sentence preventing survivors to resume normal life. Research shows a higher unemployment rate in cancer survivors as compared to the cancer-free population. Also, individual testimonies illustrate challenges in obtaining health/life insurance, loans and mortgage.
Using novel individualized algorithms, insurance companies may better define the risk of covering patients with pas history of cancer. Herein is described a novel tool to offer individualized risk assessment for patients with history of cancer.
The document discusses key concepts for evaluating diagnostic tests and techniques, including sensitivity, specificity, predictive values, and likelihood ratios. It emphasizes that diagnostic tests need to be evaluated based on their relevance, validity, and ability to help clinicians care for patients. New diagnostic tests should be properly evaluated through clinical studies using gold standard references and accounting for prevalence, blinding, and independent application of the reference standard before being adopted into routine care.
Dr. maryalice stetler stevenson b-all mrdHitham Esam
Flow cytometry plays an important role in detecting minimal residual disease (MRD) in B-cell acute lymphoblastic leukemia (B-ALL). Studies by the Children's Oncology Group (COG) determined that a level of >0.01% MRD detected by flow cytometry indicates higher risk and is clinically relevant. The COG assay uses specific antibody panels to identify and quantify residual leukemia blasts in bone marrow samples. The assay was validated across laboratories, showing the same results and prognostic value. Standardized gating strategies and analytical techniques are crucial for accurate and reproducible MRD detection by flow cytometry.
Tumor markers are substances produced by cancer cells or other cells in response to cancer that can be detected in bodily fluids or tissues. They are used to help detect, diagnose, and manage some types of cancer. More than 20 tumor markers are currently used for a wide range of cancer types, including prostate-specific antigen for prostate cancer, thyroglobulin for thyroid cancer, and alpha-fetoprotein for liver and germ cell cancers. Tumor marker levels are measured before, during, and after cancer treatment to help plan treatment, monitor response, and check for recurrence.
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Similar to Step by Step Guide to Efficacy Analysis in Solid Tumors Oncology Clinical Trials (20)
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
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STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
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It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
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Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
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Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
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3. I n t r o d u c t i o n
Page 3
European Organization Research and
Treatment for Cancer (EORTC) and others,
2000 (V1.0) and 2009 (V1.1)
RECIST CriteriaFeatures
Widely accepted and readily applied
Subject of interest – assessment of a
change in the tumor burden
Covers the whole analysis process:
data collection efficacy conclusion
Required for all the clinical trials where
ORR or PFS are study endpoints
RECIST 1.1 currently in use
5. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 5
ScreeningRequirements
Evaluation within 4 weeks before TX start
As many lesions as possible to be documented
>= 1 measurement for the lesion
All the tumors to be classified:
6. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 6
Study Eligibility
is required if ORR is a primary efficacy endpoint
(typical for Phase II studies)
can be accepted if Time to Progression
is a primary efficacy endpoint (typical for Phase III studies).
Progression Disease Definition to be clarified!
7. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 7
Methods of Tumor Assessment
Main
Chest X-Ray
Clinical Examination (CE)
Supportive
Ultrasound
Endoscopy & Laparoscopy
Tumor Markers
Cytology & Histology
8. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 8
Methods of Tumor Assessment
The same technique to be
used to one lesion at
baseline and during the
follow-up!
9. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 9
Lesions Measurability.Tumor Lesions
Measurement Characteristic -
Lesion is Measurable if LD has min size of:
10 mm by CT scan / calipers
20 mm by chest X-ray
Lesion is Non-measurable if:
LD < 10 mm by CT / calipers or LD < 20 mm by X-ray
Truly non-measurable
10. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 10
Lesions Measurability.MalignantLymph Nodes
Measurement Characteristic – because of normal
anatomical structure
Longest Diameter
Short Axis
Measurable: SA >= 15 mm by CT scan
Non-measurable: 10 mm <= SA < 15 mm by CT scan
Non-pathological: SA < 10 mm – should not be followed
11. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 11
TumorCategorization
Two separate tumor groups: and
Different follow-up approaches
Valid until the end of the study
12. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 12
Target Lesions
The largest & the most
reproducible
Measurable by definition
Representatives of all cancer-
affected organs
Max 5 in total & max 2 per organ
Documentation: LD (SA) of each lesion & Sum of Diameters.
= 25 + 15 + 18 = 58 mm
13. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 13
Non-Target Lesions
All lesions excluded from the target
Not required to be measurable
Number is not limited
Multiple lesions in the same organ in one item - Okay
Documentation: the fact of the presence is enough!
14. B a s e l i n e T u m o r D o c u m e n t a t i o n
Page 14
Non-Target Lesions. Examples
16. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 16
Time Point Response
17. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 17
Frequency of the tumor assessments
Based on the treatment schedule
and study phase
Independent of a study drug delay &
omission & interruption
Tumor evaluation after the TX end?
Depends on the study primary
endpoints
18. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 18
Target Response
Sum of Diameters
calculated
NADIR - the smallest sum of diameters reported at prior study visits
Criteria to be met
Complete Response
(CR)
All the target lesions disappeared and the lymph nodes
are non-pathological
Partial Response
(PR)
>= 30% in the Sum of Diameters compared to the BSD
Progressive disease
(PD)
>= 20% (>= 5mm) in the Sum of Diameters compared
to NADIR
Stable Disease
(SD)
No significant changes in the target lesions size
19. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 19
Target Response
Special lesions occasions
‘too small to measure’
disappeared LD = 0 mm, faintly seen LD = 5 mm
split up
LD of fragmented portions to Sum of Diameters
coalesce
a plane between lesions LD of each individual lesion
20. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 20
Example of TargetResponse
Derivation BSD = 110 mm
NADIR = 68 mm
19% Decrease from BSD
31% Increase from NADIR
Target Response is PD
NADIR = 110 mm
11% Decrease from BSD
Target Response is SD
NADIR = 99 mm
38% Decrease from BSD
Target Response is PR
NADIR = 68 mm
34% Decrease from BSD
7% Increase from NADIR
Target Response is PRNADIR - the smallest sum of
diameters reported at prior study visits
21. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 21
Non-Target Response
No quantitative
result available
Criteria to be met
Complete Response
(CR)
All the non-target lesions disappeared
All the lymph nodes are non-pathological
The tumor-marker level is normal
Non-CR/Non-PD
At least one non-target lesion is persistent OR the
tumor marker level is above normal
Progressive disease
(PD)
Unequivocal progression
22. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 22
New Lesion Appearance
Always means PD
Must be unequivocal.
Otherwise – additional evaluation!
23. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 23
OverallResponse. MeasurableDisease
Target
Response
Non-target
Response
New
Lesion
Overall
Response
CR CR No Complete Response
CR Non-CR/non-PD No Partial Response
CR NE* No Partial Response
PR Non-PD or NE* No Partial Response
SD Non-PD or NE* No Stable Disease
NE* Non-PD No Unevaluable
PD Any Yes or No Progressive Disease
Any PD Yes or No Progressive Disease
Any Any Yes Progressive Disease
* NE - Not All Evaluated
24. P o s t - B a s e l i n e T u m o r E v a l u a t i o n
Page 24
OverallResponse.
Non-Measurable Disease only
Non-target
Response
New
Lesion
Overall
Response
CR No Complete Response
Non-CR/non-PD No Non-CR/non-PD
NE* No Unevaluable
Unequivocal PD Yes or No Progressive Disease
Any Yes Progressive Disease
* NE - Not All Evaluated
26. B e s t O v e r a l l R e s p o n s e
Page 26
Best OverallResponse (BOR)
the best response across all the time points up to
the treatment/study end or the start of the new therapy
–> to be confirmed?
–> to be confirmed?
–> min time from baseline!
27. B e s t O v e r a l l R e s p o n s e
Page 27
Complete Response Confirmation
First
Time
Point
Response
Subsequent
Time
Point
Response
Best
Overall Response
(BOR)
CR Complete Response
PR
Stable Disease* or Progressive Disease** or
Partial Response
SD
Stable Disease* or Progressive Disease**
PD
NE Stable Disease* or Unevaluable**
Min time from baseline criterion: *- met,**- notmet.
28. B e s t O v e r a l l R e s p o n s e
Page 28
Partial Response Confirmation
Min time from baseline criterion: *- met,**- notmet.
First
Time
Point
Response
Subsequent
Time
Point
Response
Best
Overall Response
(BOR)
CR Partial Response
PR Partial Response
SD Stable Disease
PD Stable Disease* or Progressive Disease**
NE Stable Disease* or Unevaluable**
29. B e s t O v e r a l l R e s p o n s e
Page 29
Best OverallResponse. Example 1
Requirements:
- min SD duration - 7 weeks
- min 4 weeks between assessments to confirm BOR
Unconfirmed BOR is CR
Confirmed BOR is PR
30. B e s t O v e r a l l R e s p o n s e
Page 30
Best OverallResponse. Example2
Requirements:
min SD duration - 7 weeks
min 4 weeks between assessments to confirm BOR
Unconfirmed BOR is PR
Confirmed BOR is SD
32. O t h e r E f f i c a c y E n d p o i n t s
Page 32
33. O t h e r E f f i c a c y E n d p o i n t s
Page 33
Endpoint
Name
Start
Time Point
Event of
Interest
Censoring
Date
First PR/CR Date First PD Date
Last non-PD Tumor
Assessment Date
First Treatment /
Randomization Date
First PD Date
Last non-PD Tumor
Assessment Date
First Treatment /
Randomization Date
First PD or
Death Date
Last non-PD Tumor
Assessment Date
Time to Event Endpoints
35. C o n c l u s i o n
Page 35
All
Lesions
Identified
at
Baseline
Target
Lesions
Non-Target
Lesions
Target
Response
New
Lesions
Non-Target
Response
Overall
Responses
from Follow-up
Time Points
1-st PD
Date
SD
Duration
BOR
PFS
DOR
CBR
Time to
PD
ORR
Efficacy Analysis Process
We are living in the time when the number of cancer patients is shocking. Fortunately, from year to year cancer ceases to be a mortal diagnosis because the diagnostic methods and treatments are constantly changing and improving. Surely, in some cases cancer cannot be cured completely. However, it can be successfully controlled for many years. It has become possible due to the achievements of different pharmaceutical companies that have been working hard on discovering a treatment that will fight different types of this disease.
As mentioned in the paper title, today I am going to talk about solid tumors oncology, namely about RECIST Criteria. It is the main instrument to evaluate an objective response to the study treatment in oncology clinical trials nowadays. The abbreviation is commonly used in a clinical programmer’s daily routine but not everyone has a deep understanding of the RECIST requirements and we are going to change it right now.
At first, I was assigned to support oncology clinical trial approximately 3 years ago and, for sure, I had very many questions at that time. The worst thing was that I could not understand the efficacy data to identify data issues. What I mean now, most of us know that if the reported diastolic blood pressure is higher than the corresponding systolic blood pressure, then it is definitely a case of data issue. However, if we have some tumor measurements collected and the response that is based on these measurements, it is not so obvious to see whether the response has been defined correctly.
So, what is the RECIST? – Response Evaluation Criteria in Solid Tumors. It is the widely accepted and readily applied standard criteria used in the majority of oncology clinical trials today. The main object of the RECIST Guideline is the assessment of changes in the anatomical tumor burden during the study follow-up.
The criteria are required to be applied to all clinical trials where the Objective Response or Progression-Free Survival are in the list of the study endpoints.
The Guideline provides with the details of efficacy analysis in solid tumors oncology studies starting from the data collection process and up to the final RECIST compliant statistical results
Two versions of RECIST criteria have been provided so far by the European Organization Research and Treatment for Cancer in collaboration with other organizations. Version 1.0 in 2000 and version 1.1 in the 2009. The latter one is the most up-to-date and has been described in the paper.
Now let us talk about RECIST 1.1 it in details. The first point is Baseline Tumor Documentation.
To ensure the most honest tumor response RECIST1.1 gives some requirements to take into account at baseline.
Namely, all the evaluations should be done as close to the study treatment start as possible and never more than 4 weeks before the beginning of the treatment.
As many lesions presented at baseline as possible should be documented per patient. The study protocol can contain the list of organ sites for obligatory evaluation at baseline defined by the type of cancer investigated in a particular clinical trial.
Each lesion must be accurately measured in at least one direction and all the measurements should be recorded in a metric notation.
Then, all the examined tumor lesions and lymph nodes must be categorized as measurable or non-measurable.
If at least one measurable lesion is present, it is said that the patient has a Measurable Disease, otherwise the patient has a Non-Measurable disease only.
In case the objective tumor response is a study primary endpoint, only patients with a measurable disease can be involved in the efficacy analysis.
However, if primary endpoints include only the time to tumor progression, the study protocol must specify whether the patients without a measurable disease are also eligible.
Since the restriction to a measurable disease may slow down the recruitment to the study, trials often allow entering both types of patients. In such cases, the protocol should contain the description of findings that could be classified as the disease progression for patients with only a non-measurable disease.
The slide shows all possible methods of tumor assessments. The best currently available and reproducible methods to evaluate a tumor size are CT and MRI. Also X-Ray and Clinical examination can be used.
What you really need to know about the method of tumor assessment is that RECIST requires the same technique of assessment to be used to describe each particular lesion at baseline and during the follow-up. This will ensure the most accurate and meaningful feedback.
Now let us look at the concept of measurability. RECIST 1.1 suggests two different approaches, namely for the lesions other than lymph nodes and for lymph nodes separately.
I am going to start from the tumor lesions that are not lymph nodes.
The Longest Diameter should be used as a measurement characteristic of all of them. Measurability criterion depends on the method of the tumor assessment. A measurable tumor lesion is defined as a lesion with the minimum size of 10 mm by CT scan or caliper and 20 mm by chest X-ray.
All the other lesions are considered non-measurable. These are small lesions with the longest diameter less than 10 mm as well as the lesions that cannot be accurately measured with caliper or imaging techniques. The latter ones are called truly non-measurable.
Unlike other tumor types, a short axis is used as a measurement characteristic of lymph nodes. Such a decision has been made in order to provide with a more objective measurement since the lymph nodes are normal anatomical structures, which may be visible by imaging even if a lymph node does not contain any tumor cells.
In the picture, there is an example of nodal measurement. The nodal size is normally reported in two dimensions. The longest of these measures is called the longest diameter and the smallest of them is the short axis.
RECIST 1.1 gives the following idea of lymph nodes classification:
Malignant lymph nodes with the short axis 15 mm or longer when assessed by CT scan are considered measurable. All the other lymph nodes with the short axis between 10 and 15 mm are presumed to be non-measurable. Nodes with the short axis less than 10 mm are non-pathological and should not be recorded or followed.
As soon as lesions measurability have been documented, the next step is to divide all the tumors into two separate groups - target and non-target.
This step is important, since different approaches will be used to follow-up each of the types.
The classification will be valid until the study discontinuation. It means that a tumor defined as target at baseline cannot become non-target during the follow-up and vice versa.
The target lesions are selected based on the tumors size and their suitability for accurately repeated measurements.
It can be the case that the largest lesion is not suitable for the follow-up because of the unstable configuration.
Therefore, the largest most reproducible measurable lesions up to a maximum of two per organ and five in total should be defined as target lesions and recorded at baseline.
The target lesions should be represented in as many cancer-affected organs as possible.
As soon as the list of target lesions is prepared, a baseline sum of the diameters should be calculated.
BSD includes the longest diameter for non-nodal lesions and a short axis for nodes. It will be used as a reference to describe post-baseline target lesions responses.
The examples of target lesions and BSD calculation can be seen in the slide.
All the other lesions that have not been defined as target should be identified as non-target lesions.
Their number is not limited and it is allowed to report multiple non-target lesions located in the same organ as a single item.
Although some non-target lesions may actually be measurable, they should be reported only qualitatively, so the fact of presence at baseline is enough.
In the slide, you can also see examples of non-target lesions.
In this slide, you can also see examples of non-target lesions: non-measurable, cystic, located in previously treated area and so on.
This is the end of the baseline tumors documentation process. Let us see what is going on during post-baseline visits.
A post-baseline response of the oncology disease itself is called Overall Response.
It is based on three main factors, namely, target disease response, non-target disease response, and the appearance of new lesions.
The frequency of the tumor evaluation depends on the study phase and schedule of the treatment, and should not be affected by a study drug delay, omission or interruption.
The necessity and frequency of tumor evaluation after the end of the study therapy depends on the study endpoints.
The first thing to discuss is Target Lesions Response.
Similar to what has been done at baseline, the longest diameter or short axis of each target lesion should be measured and added to the Sum of Diameters.
Then RECIST 1.1 suggests considering Complete Response if all target non-nodal lesions disappeared and all lymph nodes became non-pathological.
Partial Response should be reported if there is at least 30% decrease in the Sum of Diameters comparing to Baseline.
Progressive disease is documented if Sum of Diameters increased by 20% or more comparing to the smallest sum of diameters reported at prior study visits that is called NADIR. The increase should be at least 5 mm.
Otherwise, if there was no significant Sum of Diameters changes, Stable Disease is assumed.
Sometimes target lesion may become too faint that it is impossible to provide an exact measure.
In such a case ‘too small to measure’-status is reported with one of the default values for the diameter: 0 mm if the lesion is likely to have disappeared, or 5 mm if the lesion is still faintly seen.
If non-nodal target lesion has split up, the longest diameters of the fragmented portions should be added to the Sum of Diameters.
If the lesions coalesce, a plane between them may be used to measure the diameter of each individual lesion.
Here you can see how Target Response is defined. Let us look at the visit Week 24 in details:
Sum of the Diameters is 73 mm,
Baseline Sum is 110 mm,
The best prior reported result is 68 mm.
This means 34 % Decrease from Baseline and 7% Increase from NADIR. Looking to the previous table, we consider Partial Response.
The definition of the Non-target response is not so transparent since no numeric results are reported for non-target lesions.
RECIST 1.1 says that Complete Response should be concluded if all non-target tumors disappeared, lymph nodes became non-pathological, and tumor marker level is normal.
Non-Complete Response/ Non–Progressive Disease status takes place if at least one non-target lesion is visible or tumor marker level is above normal.
Otherwise, Unequivocal Progression should be reported.
Usually, a minor tumor size increase is not sufficient to report unequivocal progression. There must be such overall substantial worsening in a non-target disease that even providing target response is SD or PR, the overall tumor burden has increased sufficiently.
The appearance of a new lesion always means disease progression, so it should be carefully defined. The finding should be unequivocal and not related to the differences in the scanning technique. Otherwise, if a new lesion is equivocal because of its small size or any other reason, an additional evaluation is recommended.
A lesion identified in a location that was not examined at baseline should be considered a new one as well.
As soon as the Target and Non-target responses are received and all the new lesions documented, Overall Response can be defined. Two fundamentally different cases are described in the RECIST 1.1 Guideline.
The first one is when the patient has a Measurable Disease and you can see it in the slide now.
The most important point is that the Progression in at least one of the three components gives the Overall Response equal to PD.
Complete response can be concluded only if both the target and non-target tumors show Complete Response and no new lesion has been found.
Concerning the situation when not all target tumors have been evaluated, it is likely to lead to Unevaluable Overall Response. However, Overall Disease Progression can be reported if it is clear that the contribution of non-assessed lesions would not influence the response.
In the second case, when no measurable disease is available, the algorithm is much easier. Note that the list of possible overall responses is different since no Partial Response can be claimed. In addition, Non-Complete Response/Non-Progressive Disease Status is used instead of Stable Disease Response.
Finally, when all the time point responses are collected, we can switch to efficacy endpoints derivations. The first point is Best Overall Response.
The best overall response is the best response reported for the patient during the treatment or study period depending on what is said in the protocol.
The period can be shortened by the start of additional cancer therapy before disease progression.
If a Stable Disease is assumed as BOR, it must meet the minimum time from baseline criterion, generally 6 - 8 weeks. If the time minimum has not been achieved, the response should be defined based on the subsequent assessment. If there is no subsequent assessment available, BOR should be considered unevaluable.
Depending on the study requirements, Complete and Partial Responses may need a confirmation. RECIST 1.1 recommends using confirmation for clinical trials without a control group or for the studies where the objective response rate is a primary efficacy endpoint. The idea of the confirmation is that the BOR should be derived taking into account a subsequent time point assessment result. Sufficient subsequent assessments for BOR confirmation should be performed no less than 4 weeks in between.
The confirmation scheme for Complete Response is now in the slide. It is quite straightforward except for the case when Complete Response had been reported at the first time point but was not confirmed on a subsequent visit, so Partial Response has been reported. The problem is that even Partial Response, which was met at the subsequent time point, would mean disease progression comparing to the previous result. In fact, three outcomes are possible. If minimum duration criterion for Stable Disease was met, then Stable Disease would be reported, otherwise – Progressive Disease.
Nevertheless, sometimes the subsequent scan may clarify that small lesions are still in place but not measurable any longer. This would mean that at the first time point the patient experienced a Partial, but not Complete Response. In this case, BOR should be set to Partial Response.
In the next slide, you can see the confirmation scheme for Partial Response case but it is similar to the Complete Response case.
This slide provides you with an example of the Best Overall Response Definition.
Let us assume that the tumor evaluations were repeated each 8 weeks. The minimum criterion for SD duration is 7 weeks. Subsequent assessments sufficient for BOR confirmation should be performed no less than 4 weeks in between.
In this example, Unconfirmed BOR is Complete Response while Confirmed BOR is Partial Response. The reason is no record to confirm CR is available but there are two consequent PR observations with more than 28 days in between.
In the second example, Unconfirmed BOR is Partial Response, while Confirmed BOR is Stable Disease. The reason is no record to confirm PR is available but the first PR assessment has met minimum criterion for stable disease duration.
Finally, we are going to have a quick look at the other efficacy endpoints that could be derived using RECIST compliant data.
First two ones are based on the BOR results.
Objective Response Rate is the ratio of the patients with the Best Overall Response equal to Complete or Partial Response to the total number of patients.
Clinical Benefit Rate is the ratio of the patients with the Best Overall Response equal to Complete Response, Partial Response or Stable Disease to the total number of patients.
Time to event analysis is a powerful statistical instrument widely used in oncology clinical trials.
The list of target endpoints includes progression free survival, duration of response and duration of stable disease.
Unfortunately, there is not enough time to discuss it in details but you can find some additional information in my paper.
Now it is time to sum up.
We have discussed the whole process of the RECIST compliant efficacy analysis in solid tumors oncology clinical trials. You can see all the steps that we have covered in the picture. We started from the baseline tumor assessments, and then continued with tumors categorization, follow up evaluations, overall response definition, and finished with the efficacy endpoints derivations.
Thanks for your attention! Any questions are welcome!