This document discusses the evaluation of diagnostic tests. It defines key terms used to evaluate tests such as sensitivity, specificity, predictive values, and likelihood ratios. It provides examples of evaluating a fine needle aspiration test for breast cancer using these measures. The document also discusses how prevalence of a disease can impact predictive values and compares two-stage versus simultaneous testing approaches.
Likelihood Ratio, ROC and kappa Statisticsamitakashyap1
A 57-year-old man presents with progressively worsening low back pain, numbness in his right buttock and thigh, and weakness in his right lower limb. His temperature is elevated and he has tenderness in his lower back and decreased sensation in his right foot. The doctor suspects a 20% chance of spinal malignancy. While an MRI has higher sensitivity and specificity for diagnosis, the doctor considers whether to do an ESR or directly order an MRI. Using a 2x2 table method with the sensitivity and specificity of ESR, the doctor calculates that a positive ESR would increase the probability of malignancy from 20% to 37%.
Screening of Diseases_Community Medicine
Slides may be referred by both undergraduate and postgraduate students and anyone affiliated to Public health.
Any comments or doubts may be addressed to vineeta1992@gmail.com
The document discusses medical testing and how to interpret test results. It explains that all medical tests have limitations and can produce false positives or false negatives. It emphasizes that the sensitivity and specificity of a test must be determined based on appropriate study populations that represent the full spectrum of disease. Most importantly, predictive values are needed to properly interpret individual test results, as these take into account the likelihood of disease before the test.
This document discusses key concepts regarding diagnostic and screening tests. It covers validity measures like sensitivity, specificity, predictive values, and receiver operating characteristic curves. It also addresses reliability through percent agreement and kappa statistics. The document contrasts sequential versus simultaneous use of multiple tests and examines how prevalence impacts predictive values. Finally, it outlines important factors for evaluating screening tests such as disease characteristics, test properties, and societal considerations.
This document discusses the validity and reliability of analytical tests used for screening and diagnosis. It defines key terms like sensitivity, specificity, predictive value and discusses how changing cutoff levels can impact false positives and negatives. Screening tests are used to separate populations into those with and without a disease, while considering a test's accuracy. Continuous variable tests may require an artificial cutoff versus dichotomous screening tests. The document also examines how prevalence impacts predictive value and how using multiple screening tests can improve accuracy.
This document discusses screening and its key aspects. It defines screening as identifying unrecognized disease through simple tests applied rapidly to large populations. Screening is important because many diseases present asymptomatically initially. The document contrasts screening tests with diagnostic tests, and describes different types of screening like mass, high-risk, and opportunistic screening. It outlines criteria for introducing screening programs and evaluating screening tests. Factors that impact screening test validity, biases in screening evaluations, and the ethics and economics of screening are also covered briefly.
The document discusses risk assessment and various measures used to quantify risk such as relative risk, attributable risk, odds ratio, prevalence rate, and incidence rate. It provides examples of how to calculate these measures from cohort and case-control study data and interpret the results. Key points are that relative risk is used for cohort and experimental studies, odds ratio for case-control studies, and prevalence and incidence rates help measure disease burden. Attributable risk helps identify excess risk from an exposure. The examples help illustrate how to apply these concepts to public health practice.
Medical Decision Making associated with Clinical test interpretations. Depending on the situation one should get a second test to confirm the result of the first one; or one should move on to the treatment phase.
Likelihood Ratio, ROC and kappa Statisticsamitakashyap1
A 57-year-old man presents with progressively worsening low back pain, numbness in his right buttock and thigh, and weakness in his right lower limb. His temperature is elevated and he has tenderness in his lower back and decreased sensation in his right foot. The doctor suspects a 20% chance of spinal malignancy. While an MRI has higher sensitivity and specificity for diagnosis, the doctor considers whether to do an ESR or directly order an MRI. Using a 2x2 table method with the sensitivity and specificity of ESR, the doctor calculates that a positive ESR would increase the probability of malignancy from 20% to 37%.
Screening of Diseases_Community Medicine
Slides may be referred by both undergraduate and postgraduate students and anyone affiliated to Public health.
Any comments or doubts may be addressed to vineeta1992@gmail.com
The document discusses medical testing and how to interpret test results. It explains that all medical tests have limitations and can produce false positives or false negatives. It emphasizes that the sensitivity and specificity of a test must be determined based on appropriate study populations that represent the full spectrum of disease. Most importantly, predictive values are needed to properly interpret individual test results, as these take into account the likelihood of disease before the test.
This document discusses key concepts regarding diagnostic and screening tests. It covers validity measures like sensitivity, specificity, predictive values, and receiver operating characteristic curves. It also addresses reliability through percent agreement and kappa statistics. The document contrasts sequential versus simultaneous use of multiple tests and examines how prevalence impacts predictive values. Finally, it outlines important factors for evaluating screening tests such as disease characteristics, test properties, and societal considerations.
This document discusses the validity and reliability of analytical tests used for screening and diagnosis. It defines key terms like sensitivity, specificity, predictive value and discusses how changing cutoff levels can impact false positives and negatives. Screening tests are used to separate populations into those with and without a disease, while considering a test's accuracy. Continuous variable tests may require an artificial cutoff versus dichotomous screening tests. The document also examines how prevalence impacts predictive value and how using multiple screening tests can improve accuracy.
This document discusses screening and its key aspects. It defines screening as identifying unrecognized disease through simple tests applied rapidly to large populations. Screening is important because many diseases present asymptomatically initially. The document contrasts screening tests with diagnostic tests, and describes different types of screening like mass, high-risk, and opportunistic screening. It outlines criteria for introducing screening programs and evaluating screening tests. Factors that impact screening test validity, biases in screening evaluations, and the ethics and economics of screening are also covered briefly.
The document discusses risk assessment and various measures used to quantify risk such as relative risk, attributable risk, odds ratio, prevalence rate, and incidence rate. It provides examples of how to calculate these measures from cohort and case-control study data and interpret the results. Key points are that relative risk is used for cohort and experimental studies, odds ratio for case-control studies, and prevalence and incidence rates help measure disease burden. Attributable risk helps identify excess risk from an exposure. The examples help illustrate how to apply these concepts to public health practice.
Medical Decision Making associated with Clinical test interpretations. Depending on the situation one should get a second test to confirm the result of the first one; or one should move on to the treatment phase.
This document discusses principles of radiation therapy and dose selection for various conditions. It provides guidelines for selecting marginal doses for different tumor types based on location and size, including doses of 12-13 Gy for acoustic neuromas, 16-25 Gy for pituitary adenomas, 12-15 Gy for benign meningiomas, and 20-24 Gy for arteriovenous malformations. Risk models are presented for complications after radiosurgery for brain metastases and arteriovenous malformations based on tumor location and volume. Guidelines aim to maximize tumor control while minimizing risks of complications like necrosis and cranial neuropathy.
This document provides an overview of diagnostic testing and assessing diagnostic accuracy. It defines key concepts like sensitivity, specificity, predictive values, and likelihood ratios. Sensitivity measures the ability of a test to detect true positives, or people with the disease. Specificity measures the ability to detect true negatives, or people without the disease. Positive and negative predictive values depend on disease prevalence and estimate the probability of actual disease given a test result. Likelihood ratios quantify how much a test result changes the odds of disease. The document uses examples to demonstrate calculating and interpreting these performance measures.
Contemporary Management of HIV. New Data From IDWeek 2018 and Other Fall 2018...hivlifeinfo
Contemporary Management of HIV. New Data From IDWeek 2018 and Other Fall 2018 HIV Conferences
Format: Microsoft PowerPoint (.ppt)
File Size: 690 KB
Released: December 5, 2018
Screening tests involve applying simple tests to apparently healthy people to identify those likely to have a disease. An ideal screening test is valid, reliable, and meets specific criteria. Validity is measured by sensitivity, which is the test's ability to detect true positive cases, and specificity, which is its ability to exclude true negative cases. Reliability means the test gives consistent results under the same conditions. Screening can help detect disease early when treatment is more effective, but accuracy is crucial to avoid false positives and negatives. Research carefully evaluates new screening tests against a gold standard to understand their performance.
Cs in Naser Medical Complx- Gaza - PalestineWaled Abohatab
The document summarizes a study on rising cesarean section rates at Nasser Medical Complex from 2011-2013. The most common indications for C-section were previous C-sections (30%), previous one C-section (24%), breech presentation (13%), and fetal distress (5%). Recommendations include strategies to reduce primary C-sections, careful patient selection for breech deliveries, and avoiding continuous fetal monitoring for low-risk patients. The overall C-section rate was found to be rising, with maternal and neonatal risks requiring further extended study.
A 57-year-old man presents with progressively worsening low back pain, numbness in his right buttock and thigh, and weakness in his right lower limb. His temperature is elevated and he has tenderness in his lower back and decreased sensation in his right foot. The doctor suspects a 20% chance of spinal malignancy. ESR has 78% sensitivity and 67% specificity for detection, while MRI has 95% sensitivity and 95% specificity. Using the 2x2 table method and likelihood ratios, the doctor determines that a positive ESR would increase the probability of malignancy from 20% to 37%, while a positive MRI would increase it to 92%.
Validity refers to how accurately a screening test measures a disease. Key measures of validity include sensitivity, specificity, and predictive value. Sensitivity measures the percentage of true positives, specificity measures the percentage of true negatives, and predictive value refers to the probability that the test result correctly identifies whether someone has the disease or not. The prevalence of a disease in a population also affects the predictive power of screening tests. Combining multiple screening tests can increase overall sensitivity and specificity for more accurate disease detection.
Diagnostic, screening tests, differences and applications and their characteristics, four pillars of screening tests, sensitivity, specificity, predictive values and accuracy
This document discusses screening and diagnostic tests. It defines screening and diagnostic tests as tools used to distinguish people who have a disease from those who do not. The quality and accuracy of these tests is important to understand. Tests are evaluated based on their sensitivity, specificity, predictive values, and likelihood ratios compared to a gold standard. Factors like disease prevalence can impact predictive values. Receiver operating characteristic curves are used to evaluate test performance across all thresholds. Screening tests aim to identify disease early but must account for biases and show effectiveness of interventions.
The document discusses the uncertainty inherent in medical diagnosis and treatment. It notes that diagnoses assign probabilities rather than certainties, and that tests have varying sensitivity and specificity levels. A key challenge is determining acceptable risk levels, such as how many missed diagnoses are tolerable. The document advocates considering pre-test probability, test accuracy metrics, and residual risk to determine appropriate diagnostic or discharge pathways. Overall, it emphasizes communicating risk to patients and balancing risk versus benefit in clinical decision making.
John Tidy - Adjunctive colposcopic technologiestriumphbenelux
This document discusses various adjuvant colposcopy technologies that can help improve the performance of colposcopy. It notes that the prevalence of disease impacts colposcopy performance and new screening methods may increase women with low disease risk being referred. Several technologies are presented that could help by increasing sensitivity to detect HG-CIN, improving specificity to guide biopsies, and providing reassurance when results are normal. Technologies discussed include LuViva, DySIS, ZedScan, and TruScreen, with some clinical data presented on their ability to improve CIN detection compared to colposcopy alone. The document advocates for using such technologies to help colposcopy adapt to changes in screening populations.
This document discusses screening tests and their evaluation. It defines screening as applying a test to asymptomatic individuals to identify those at high risk of disease. Key criteria for diseases suitable for screening include being a major health problem, having a recognizable pre-symptomatic stage, and having effective early treatment. Important features of screening tests are that they are reliable, sensitive, specific, acceptable and inexpensive. Sensitivity measures the test's ability to correctly identify those with disease, while specificity measures its ability to correctly identify those without disease. Predictive values indicate the likelihood that individuals with positive or negative test results truly have or do not have the disease.
Epidemiological method to determine utility of a diagnostic testBhoj Raj Singh
The usefulness of diagnostic tests, that is their ability to detect a person with disease or exclude a person without disease, is usually described by terms such as sensitivity, specificity, positive predictive value and negative predictive value (NPV). Many clinicians are frequently unclear about the practical application of these terms (1). The traditional method for teaching these concepts is based on the 2 × 2 table (Table 1). A 2 × 2 table shows results after both a diagnostic test and a definitive test (gold standard) have been performed on a pre-determined population consisting of people with the disease and those without the disease. The definitions of sensitivity, specificity, positive predictive value and NPV as expressed by letters are provided in Table 1. While 2 × 2 tables allow the calculations of sensitivity, specificity and predictive values, many clinicians find it too abstract and it is difficult to apply what it tries to teach into clinical practice as patients do not present as ‘having disease’ and ‘not having disease’. The use of the 2 × 2 table to teach these concepts also frequently creates the erroneous impression that the positive and NPVs calculated from such tables could be generalized to other populations without regard being paid to different disease prevalence. New ways of teaching these concepts have therefore been suggested.
The ppt is a short description about how to ascertain the validity, ie; sensitivity and specificity of a screening test as well as their predictive powers. you can also find the technique to ascertain the best possible screening test through the help of an ROC curve...
Here are the calculations for the predictive values of a positive HIV test with 95% sensitivity and 98% specificity in populations with different prevalence rates:
1) Prevalence of HIV in blood donors = 2%
Total tested = 1000
With HIV = 1000 * 0.02 = 20
Without HIV = 1000 - 20 = 980
Sensitivity = 95%
Specificity = 98%
True Positives (a) = Sensitivity * With HIV = 0.95 * 20 = 19
False Positives (b) = (1 - Specificity) * Without HIV = 0.02 * 980 = 20
False Negatives (c) = (1 - Sensitivity) * With HIV = 0
Here are the calculations for the predictive values of a positive HIV test with 95% sensitivity and 98% specificity in populations with different prevalence rates:
1) Prevalence of HIV in blood donors = 2%
Total tested = 1000
With HIV = 1000 * 0.02 = 20
Without HIV = 1000 - 20 = 980
Sensitivity = 95%
Specificity = 98%
True Positives (a) = Sensitivity * With HIV = 0.95 * 20 = 19
False Positives (b) = (1 - Specificity) * Without HIV = 0.02 * 980 = 20
False Negatives (c) = (1 - Sensitivity) * With HIV = 0
Participants of the workshop learn the necessary background information and techniques to diagnose Sars-CoV-2 using the mobile diagnostic laboratory. The laboratory is shipped ready to use with all devices, reagents, certificates, and protocols. After one day of preparation together with a local assistant, a five-day course is given where every step is carried out by each participant. Experts accompany the learning process with written teaching materials, video training, virtual live coaching, and short exams to verify the learned content.
The document discusses evaluating diagnostic tests and summarizes key points in 3 sentences:
Diagnostic tests are evaluated based on their sensitivity, specificity, predictive values, and likelihood ratios to determine how well they identify disease when compared to a gold standard test. The performance of diagnostic tests depends on the prior probability or prevalence of the disease in the population being tested. Receiver operating characteristic (ROC) curves can be used to visualize and compare the performance of diagnostic tests by plotting the true positive rate against the false positive rate at various threshold settings.
CAT 1 -MPH 5101 - FOUNDATIONS OF EPIDEMIOLOGY (1).pptxShafici Almis
1. Validity and reliability are important concepts for evaluating diagnostic and screening tests. Validity refers to a test's ability to accurately measure what it is intended to, while reliability is its consistency.
2. Key validity measures include sensitivity (ability to correctly identify those with the disease), specificity (ability to correctly identify those without the disease), and use of a gold standard for comparison.
3. Reliability is assessed through measures like positive and negative predictive values, which indicate the probability that a positive or negative test result accurately reflects disease status. Contingency tables allow calculating these measures from data on true positives, false positives, and other outcomes.
This document discusses principles of radiation therapy and dose selection for various conditions. It provides guidelines for selecting marginal doses for different tumor types based on location and size, including doses of 12-13 Gy for acoustic neuromas, 16-25 Gy for pituitary adenomas, 12-15 Gy for benign meningiomas, and 20-24 Gy for arteriovenous malformations. Risk models are presented for complications after radiosurgery for brain metastases and arteriovenous malformations based on tumor location and volume. Guidelines aim to maximize tumor control while minimizing risks of complications like necrosis and cranial neuropathy.
This document provides an overview of diagnostic testing and assessing diagnostic accuracy. It defines key concepts like sensitivity, specificity, predictive values, and likelihood ratios. Sensitivity measures the ability of a test to detect true positives, or people with the disease. Specificity measures the ability to detect true negatives, or people without the disease. Positive and negative predictive values depend on disease prevalence and estimate the probability of actual disease given a test result. Likelihood ratios quantify how much a test result changes the odds of disease. The document uses examples to demonstrate calculating and interpreting these performance measures.
Contemporary Management of HIV. New Data From IDWeek 2018 and Other Fall 2018...hivlifeinfo
Contemporary Management of HIV. New Data From IDWeek 2018 and Other Fall 2018 HIV Conferences
Format: Microsoft PowerPoint (.ppt)
File Size: 690 KB
Released: December 5, 2018
Screening tests involve applying simple tests to apparently healthy people to identify those likely to have a disease. An ideal screening test is valid, reliable, and meets specific criteria. Validity is measured by sensitivity, which is the test's ability to detect true positive cases, and specificity, which is its ability to exclude true negative cases. Reliability means the test gives consistent results under the same conditions. Screening can help detect disease early when treatment is more effective, but accuracy is crucial to avoid false positives and negatives. Research carefully evaluates new screening tests against a gold standard to understand their performance.
Cs in Naser Medical Complx- Gaza - PalestineWaled Abohatab
The document summarizes a study on rising cesarean section rates at Nasser Medical Complex from 2011-2013. The most common indications for C-section were previous C-sections (30%), previous one C-section (24%), breech presentation (13%), and fetal distress (5%). Recommendations include strategies to reduce primary C-sections, careful patient selection for breech deliveries, and avoiding continuous fetal monitoring for low-risk patients. The overall C-section rate was found to be rising, with maternal and neonatal risks requiring further extended study.
A 57-year-old man presents with progressively worsening low back pain, numbness in his right buttock and thigh, and weakness in his right lower limb. His temperature is elevated and he has tenderness in his lower back and decreased sensation in his right foot. The doctor suspects a 20% chance of spinal malignancy. ESR has 78% sensitivity and 67% specificity for detection, while MRI has 95% sensitivity and 95% specificity. Using the 2x2 table method and likelihood ratios, the doctor determines that a positive ESR would increase the probability of malignancy from 20% to 37%, while a positive MRI would increase it to 92%.
Validity refers to how accurately a screening test measures a disease. Key measures of validity include sensitivity, specificity, and predictive value. Sensitivity measures the percentage of true positives, specificity measures the percentage of true negatives, and predictive value refers to the probability that the test result correctly identifies whether someone has the disease or not. The prevalence of a disease in a population also affects the predictive power of screening tests. Combining multiple screening tests can increase overall sensitivity and specificity for more accurate disease detection.
Diagnostic, screening tests, differences and applications and their characteristics, four pillars of screening tests, sensitivity, specificity, predictive values and accuracy
This document discusses screening and diagnostic tests. It defines screening and diagnostic tests as tools used to distinguish people who have a disease from those who do not. The quality and accuracy of these tests is important to understand. Tests are evaluated based on their sensitivity, specificity, predictive values, and likelihood ratios compared to a gold standard. Factors like disease prevalence can impact predictive values. Receiver operating characteristic curves are used to evaluate test performance across all thresholds. Screening tests aim to identify disease early but must account for biases and show effectiveness of interventions.
The document discusses the uncertainty inherent in medical diagnosis and treatment. It notes that diagnoses assign probabilities rather than certainties, and that tests have varying sensitivity and specificity levels. A key challenge is determining acceptable risk levels, such as how many missed diagnoses are tolerable. The document advocates considering pre-test probability, test accuracy metrics, and residual risk to determine appropriate diagnostic or discharge pathways. Overall, it emphasizes communicating risk to patients and balancing risk versus benefit in clinical decision making.
John Tidy - Adjunctive colposcopic technologiestriumphbenelux
This document discusses various adjuvant colposcopy technologies that can help improve the performance of colposcopy. It notes that the prevalence of disease impacts colposcopy performance and new screening methods may increase women with low disease risk being referred. Several technologies are presented that could help by increasing sensitivity to detect HG-CIN, improving specificity to guide biopsies, and providing reassurance when results are normal. Technologies discussed include LuViva, DySIS, ZedScan, and TruScreen, with some clinical data presented on their ability to improve CIN detection compared to colposcopy alone. The document advocates for using such technologies to help colposcopy adapt to changes in screening populations.
This document discusses screening tests and their evaluation. It defines screening as applying a test to asymptomatic individuals to identify those at high risk of disease. Key criteria for diseases suitable for screening include being a major health problem, having a recognizable pre-symptomatic stage, and having effective early treatment. Important features of screening tests are that they are reliable, sensitive, specific, acceptable and inexpensive. Sensitivity measures the test's ability to correctly identify those with disease, while specificity measures its ability to correctly identify those without disease. Predictive values indicate the likelihood that individuals with positive or negative test results truly have or do not have the disease.
Epidemiological method to determine utility of a diagnostic testBhoj Raj Singh
The usefulness of diagnostic tests, that is their ability to detect a person with disease or exclude a person without disease, is usually described by terms such as sensitivity, specificity, positive predictive value and negative predictive value (NPV). Many clinicians are frequently unclear about the practical application of these terms (1). The traditional method for teaching these concepts is based on the 2 × 2 table (Table 1). A 2 × 2 table shows results after both a diagnostic test and a definitive test (gold standard) have been performed on a pre-determined population consisting of people with the disease and those without the disease. The definitions of sensitivity, specificity, positive predictive value and NPV as expressed by letters are provided in Table 1. While 2 × 2 tables allow the calculations of sensitivity, specificity and predictive values, many clinicians find it too abstract and it is difficult to apply what it tries to teach into clinical practice as patients do not present as ‘having disease’ and ‘not having disease’. The use of the 2 × 2 table to teach these concepts also frequently creates the erroneous impression that the positive and NPVs calculated from such tables could be generalized to other populations without regard being paid to different disease prevalence. New ways of teaching these concepts have therefore been suggested.
The ppt is a short description about how to ascertain the validity, ie; sensitivity and specificity of a screening test as well as their predictive powers. you can also find the technique to ascertain the best possible screening test through the help of an ROC curve...
Here are the calculations for the predictive values of a positive HIV test with 95% sensitivity and 98% specificity in populations with different prevalence rates:
1) Prevalence of HIV in blood donors = 2%
Total tested = 1000
With HIV = 1000 * 0.02 = 20
Without HIV = 1000 - 20 = 980
Sensitivity = 95%
Specificity = 98%
True Positives (a) = Sensitivity * With HIV = 0.95 * 20 = 19
False Positives (b) = (1 - Specificity) * Without HIV = 0.02 * 980 = 20
False Negatives (c) = (1 - Sensitivity) * With HIV = 0
Here are the calculations for the predictive values of a positive HIV test with 95% sensitivity and 98% specificity in populations with different prevalence rates:
1) Prevalence of HIV in blood donors = 2%
Total tested = 1000
With HIV = 1000 * 0.02 = 20
Without HIV = 1000 - 20 = 980
Sensitivity = 95%
Specificity = 98%
True Positives (a) = Sensitivity * With HIV = 0.95 * 20 = 19
False Positives (b) = (1 - Specificity) * Without HIV = 0.02 * 980 = 20
False Negatives (c) = (1 - Sensitivity) * With HIV = 0
Participants of the workshop learn the necessary background information and techniques to diagnose Sars-CoV-2 using the mobile diagnostic laboratory. The laboratory is shipped ready to use with all devices, reagents, certificates, and protocols. After one day of preparation together with a local assistant, a five-day course is given where every step is carried out by each participant. Experts accompany the learning process with written teaching materials, video training, virtual live coaching, and short exams to verify the learned content.
The document discusses evaluating diagnostic tests and summarizes key points in 3 sentences:
Diagnostic tests are evaluated based on their sensitivity, specificity, predictive values, and likelihood ratios to determine how well they identify disease when compared to a gold standard test. The performance of diagnostic tests depends on the prior probability or prevalence of the disease in the population being tested. Receiver operating characteristic (ROC) curves can be used to visualize and compare the performance of diagnostic tests by plotting the true positive rate against the false positive rate at various threshold settings.
CAT 1 -MPH 5101 - FOUNDATIONS OF EPIDEMIOLOGY (1).pptxShafici Almis
1. Validity and reliability are important concepts for evaluating diagnostic and screening tests. Validity refers to a test's ability to accurately measure what it is intended to, while reliability is its consistency.
2. Key validity measures include sensitivity (ability to correctly identify those with the disease), specificity (ability to correctly identify those without the disease), and use of a gold standard for comparison.
3. Reliability is assessed through measures like positive and negative predictive values, which indicate the probability that a positive or negative test result accurately reflects disease status. Contingency tables allow calculating these measures from data on true positives, false positives, and other outcomes.
When diagnosing a patient's problem, doctors consider clinical data and diagnostic test results. The use of diagnostic tests is increasing due to availability and new technology, though diagnostic techniques are less rigorously evaluated than treatments. For a new diagnostic test to be relevant, it must be feasible for the community and accurately diagnose the patient's condition compared to a gold standard reference. Validity is determined by comparing the test to an acceptable reference standard using a sample of over 100 patients with an appropriate range of diseases. Sensitivity and specificity are important metrics but must be interpreted with likelihood ratios which convey how much a positive or negative test result changes the probability of disease.
Application of a test or a procedure to large number of population who have no symptoms of a particular disease for the purpose of determining their likelihood of having the disease.
This document discusses concepts related to diagnostic testing in animal disease. It defines what a diagnostic test is and discusses some key issues like the presence of false positives and negatives. It describes different categories of tests, including screening tests for healthy animals and confirmatory tests for diseased animals. Key metrics for evaluating tests are explained, such as sensitivity, specificity, predictive values, and accuracy. Factors that can impact test results like cut-off points and prevalence are also covered. The document provides examples of specific tests and discusses the trade-offs of optimizing tests for sensitivity versus specificity.
Epidemiological Approaches for Evaluation of diagnostic tests.pptxBhoj Raj Singh
Diagnosis of a disease or a problem is the first step towards solution/ treatment. Clinical Diagnosis or Provisional Diagnosis is the first step in diagnosis and is done after a physical examination of the patient by a clinician. Clinical diagnosis may or may not be true and to reach Final diagnosis Laboratory Investigations using gross and microscopic pathological observations and determining the disease indicators are required. The diagnostic tests may be Non-dichotomous Diagnostic Tests (when continuous values are given by the test in a range starting from sub-normal to above-normal range) and Dichotomous Diagnostic Tests (when results are given either plus or minus, disease or no-disease). To make non- Dichotomous diagnostic test a Dichotomous one you need to establish the cut-off values based on reference values or Gold Standard test readings or with the use of Receiver operator characteristic (ROC) curves, Precision-Recall Curves, Likelihood Ratios, etc., and finally establishing statistical agreement (using Kappa values, Level of Agreement, χ2 Statistics) between the true diagnosis and laboratory diagnosis. Thereafter, the Accuracy, Precision, Bias, Sensitivity, Specificity, Positive Predictive value, and Negative Predictive value, of a diagnostic test are established for use in clinical practice. Diagnostic tests are also used to determine Prevalence (True prevalence, apparent prevalence) and Incidence of the disease to estimate the disease burden so that control measures can be implemented. There are several Phases in the development and use of a diagnostic assay starting from conceptualization of the diagnostic test, development and evaluation to determine flaws in diagnostic test use and Interpretation influencers. This presentation mainly deals with the epidemiological evaluation procedures for diagnostic tests.
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.
This document discusses the importance of clinical examination in making accurate diagnoses and discusses key metrics used to evaluate clinical tests and signs such as sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratios. It provides examples of calculating these metrics for tests to diagnose ascites and alcohol abuse. Clinical examinations are important but using metrics like sensitivity and specificity can help determine which signs and tests are most informative for a given condition.
1) In the first race, the hare sprints ahead but grows complacent and falls asleep, allowing the steady tortoise to win.
2) In the rematch, the determined hare runs consistently and wins.
3) In another rematch, the tortoise leads the hare to a river, where the hare cannot swim, allowing the tortoise to swim across and win again.
4) In the final race, the hare and tortoise work as a team, using each other's strengths to cross the finish line together faster than either could alone.
This document discusses principles and techniques for effective leadership and interpersonal relationships. It emphasizes building on one's authentic self to influence others through understanding relationships, providing purpose and motivation. It also discusses changing perceptions and mindsets, focusing on people rather than things, developing interdependence through mutual understanding and accountability, and the importance of listening, communication skills, and meeting psychological needs to develop synergistic relationships.
Effective public health communication oldamitakashyap1
Effective public health communication is essential for informing and influencing individuals and communities about important health issues. The document discusses various aspects of public health communication including defining it, the need for effective communication, principles of effective communication, challenges, and approaches like social marketing. It provides details on formative research conducted to develop a nutrition strategy in Rajasthan which included understanding audiences, behaviors, barriers and enablers. The strategy developed communication objectives and a plan for different audiences using various channels and materials. Monitoring indicators were also identified to track outcomes. Such a thorough, evidence-based approach can enable replicable and sustainable public health communication programs.
1) Cohort studies begin with groups of individuals who are alike in many ways but differ with respect to exposure to a certain factor, thought to influence the probability of occurrence of a disease or other outcome.
2) The groups are followed over time and the researchers record who does or does not develop the disease. This allows calculation of disease rates in the exposed and unexposed groups.
3) Cohort studies can provide strong evidence about whether an association reflects a causal relationship by assessing disease development over time in relation to exposure. However, selection bias and information bias must be considered.
This document discusses various study designs used in medical research, including observational and experimental designs. It describes descriptive, analytical, and interventional studies. It provides examples of case reports, case series, cross-sectional studies, case-control studies, and cohort studies. It discusses key aspects of case-control studies such as selection of cases and controls, matching, determining exposure, and analyzing results. It also covers limitations and advantages of different study designs.
Effective public health communication 5th aprilamitakashyap1
Effective public health communication is needed to promote awareness of health issues, educate about available services, change behaviors to improve health, address emergencies, and build community capacity. It should be relevant, accurate, culturally competent, accessible, and action-oriented. Types of public health communication include health education, advocacy, risk communication, and crisis communication. Social marketing uses commercial techniques to promote social causes like improving nutrition. Developing effective public health communication requires understanding the community through formative research, developing multilevel strategies, pre-testing materials, and monitoring outcomes. An example from Rajasthan developed a state-specific strategy to address undernutrition through behavior change communication targeting pregnant women, husbands, mothers-in-law and health workers
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Studies have shown that meditating for just 10-20 minutes per day can have significant positive impacts on both mental and physical health.
This document provides information on various contraceptive methods, including spacing and terminal methods. Spacing methods are used to space births or delay the first child, and include barrier methods, IUDs, hormonal methods, fertility awareness methods, and lactational amenorrhea. Terminal methods permanently stop conception and include vasectomy for men and tubal ligation for women. The document describes the composition, mode of action, effectiveness, advantages, and disadvantages of common contraceptive methods such as condoms, IUDs, oral contraceptive pills, injectables, implants, sterilization procedures, and fertility awareness methods.
This document discusses various indicators that can be used to measure health and disease in a population. It outlines different types of indicators including health status indicators like mortality and morbidity, quality of life indicators, socioeconomic indicators, health care delivery indicators, and environmental indicators. Specific measures are provided for different types of indicators, such as crude mortality rate, standardized mortality rates, incidence rate, and prevalence. The indicators can help health administrators assess problems, design health plans, and evaluate schemes. Ideal indicators should be valid, reliable, sensitive, specific, and feasible.
This document discusses concepts related to disease transmission. It defines the epidemiologic triad as requiring an agent, reservoir, mode of transmission, portal of entry and susceptible host. Modes of transmission include direct contact or indirect transmission through vehicles or vectors. Disease levels range from sporadic to endemic to epidemic or pandemic. Herd immunity is achieved through vaccination above a threshold proportion of immune individuals. Types of epidemics include common source, propagated or mixed spread. Body surfaces and routes of exposure allow entry of infectious agents.
Public health originated in the 19th century to address poor sanitary conditions and disease outbreaks. Simple public health measures like clean water and vaccination have saved more lives than medical advances. Community medicine focuses on preventing disease in populations through organized community efforts. It aims to promote health and adjust individuals and society. Public health is defined as organized efforts to prevent disease, prolong life, and promote health through surveillance, policies, education, and ensuring resources are allocated to public health. It uses technology and social sciences to identify, prevent and monitor health issues in populations.
Community medicine focuses on preventing disease and promoting public health rather than treating individual patients. It evolved from public health movements in the 19th century that emphasized sanitation and organized community efforts to improve health. Community medicine aims to keep populations healthy through measures like vaccination programs, vector control, and increasing access to resources like safe water and adequate nutrition. It has contributed greatly to reducing communicable diseases and improving health worldwide.
This document discusses key concepts in public health and community medicine. It defines public health as the science and art of preventing disease, prolonging life, and promoting health through organized community efforts. The document outlines the importance and evolution of public health interventions and movements. It also compares clinical and preventive medicine and discusses the contributions, functions, and future of community medicine and public health.
Community medicine focuses on health promotion and disease prevention at the community level through organized social action. It evolved from clinical medicine to address health issues facing entire populations. Key concepts include viewing health as an equilibrium between individuals and their environment, the importance of both preventive and curative approaches to medicine, and addressing social determinants of health. The field was influenced by developments in epidemiology, public health infrastructure, and the germ theory of disease.
Concept of sufficient cause and component causesamitakashyap1
This document discusses key epidemiological concepts related to measuring disease occurrence, including sufficient causes, component causes, risk, prevalence, and incidence rate. It provides examples to illustrate how these measures are calculated and how they relate to one another. For example, it notes that prevalence is equal to incidence multiplied by disease duration when rates are stable over time. The document also discusses problems that can arise in measuring these variables and how changes in incidence and prevalence over time can provide insights into disease dynamics.
1. An outbreak investigation was conducted to determine the source and mode of transmission of an illness that exceeded expected numbers. Interviews, specimen collection, and data analysis were performed.
2. Analysis revealed the pathogen and identified a water source as the likely mode of transmission. Over 100 cases were reported in the affected area within two weeks.
3. Recommendations included controlling the contaminated water source, strengthening surveillance, and preventing future outbreaks through improved sanitation.
This document discusses epidemiological concepts related to causation and measures of disease occurrence. It defines a sufficient cause as a minimal set of conditions that inevitably produce disease. It discusses how interactions between component causes can affect disease risk. It also covers Hill's criteria for evaluating causation. The document defines key measures used to assess disease occurrence, including risk, prevalence, and incidence rate. It provides examples to illustrate how to calculate each measure and explains how they can help guide decisions in patient care and disease prevention.
This document discusses key concepts related to disease transmission including:
1. The epidemiologic triad of an agent, host, and environment being required for disease transmission.
2. Various host, agent, and environmental factors that influence transmission risk.
3. Common modes of transmission like direct contact or indirect transmission through vehicles or vectors.
4. Key epidemiological terms like outbreak, epidemic, pandemic, and the differences between clinical and subclinical disease.
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Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
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Here is the updated list of Top Best Ayurvedic medicine for Gas and Indigestion and those are Gas-O-Go Syp for Dyspepsia | Lavizyme Syrup for Acidity | Yumzyme Hepatoprotective Capsules etc
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
2. Evaluation of a Diagnostic Test
Accuracy or Validity –
The degree to which a measurement or
study reaches a correct conclusion
determining the ‘True Status’ of the
disease
• Sensitivity and Specificity describe the
validity of the test relative to gold standard
• First step in the evaluation of a test is
determining True status of the disease
using ‘Gold Standard’ for the Test
3. Definitions
• Sensitivity – the percentage of diseased persons
having positive test
• Specificity – the percentage of Non- diseased
persons having negative test
• Predictive Value – estimation of the probability of
Dis. after test results –PPV & NPV
• PPV – %age of persons with +ve Test, having Dis.
• NPV - %age of persons with -ve Test, not having Dis
4. • The greater the sensitivity of a test, more likely
the test will detect the disease.
The test with Great Sensitivity are usefull to
rule out presence of a disease bcz -ve test will
virtually exclude the possibility that patient has
the Disease.
• The greater the specificity of a test, the more
likely it is that persons without the disease will
have –ve test.
Very specific tests often are used to confirm the
presence of a disease. If a test is highly specific;
a +ve test result would strongly suggest the
presence of the disease
5. Surgical Biopsy (Gold Standard- TRUTH)
FNA
results
Positive
Disease
(Biopsy + ve)
No Disease
(Biopsy - ve)
Total
14
8 22
Negative
1
91
92
TOTAL 15 99 114
True Positives
False Positives
False Negatives
True Negatives
Type I error
Type II error Power 1 -
Sensitivity
14/15=93%
Specificity
(91/99 = 92%)
PPV=14/22
= 64%
NPV =
91/92 = 99%
Prev = 13%
(15/114)
6. How Diagnostic Test help
• Whether the probability of Br. Ca is 13% or
64% :- further workup is required!!!
• But a –ve test result would reduce the
probability that Br. Ca is present to 1%
(100% minus NPV)
So!
Now no Biopsy…but keep watch
7. 14 8
1 91
Without Palpable Mass
Surgical Biopsy
Cancer No Cancer
FNA
Result
+
-
Total 15 99
22
92
114
113 15
8 181
Surgical Biopsy
Cancer No Cancer
FNA
Result
+
-
Total 121 196
128
189
317
With Palpable Mass
Total
Total
Prevalence = 13%
Sensitivity = 93%
Specificity = 92%
PPV = 64%
NPV = 99%
Prevalence = 38%
Sensitivity = 93%
Specificity = 92%
PPV = 88%
NPV = 96%
8. Two Stage Screening - Net Specificity
Net Sensitivity = 315/500 = 63% ( )
Net Specificity = 7600 + 1710/ 9500 =
98% ( )
Assessing the Validity and Reliability of Diagnostic and Screening Test
PPV-?
12. Two Stage vs Simultaneous Testing
• Compared with either test alone, there is :-
– a loss in Net Sensitivity and a gain in Net Specificity
in Two Stage Testing
– a gain in Net Sensitivity and a loss in Net Specificity
in Simultaneous Testing
• Decision to use either Two Stage or Simultaneous
Testing depends on objective and practical
considerations (like reducing hospital stay, cost
and invasiveness ! Insurance coverage)
14. Without palpable masses; Prevalence= 13%
With palpable masses; Prevalence= 38%
Prevalence= 13%
Sensitivity = 93%
Specificity = 92%
PV + = 64%
PV - = 99%
Prevalence= 38%
Sensitivity = 93%
Specificity = 92%
PV + = 88%
PV - = 96%
Predictive value and Prev.
Surgical biopsy
FNA
results
positive
Cancer No
Cancer
Total
41 5 46
negative 3 65 68
Total 44 70 114
Surgical biopsy
FNA
results
positive
Cancer No
Cancer
Total
14 8 22
negative 1 91 92
Total 15 99 114
15. Suspicious FNA results considered positive
Prevalence= 38%
Sensitivity = 93%
Specificity = 92%
PV + = 88%
PV - = 96%
Surgical biopsy
FNA
results
Positive
Cancer No Cancer Total
33 0 33
negative 11 70 81
Total 44 70 114
Suspicious FNA results considered negative
Prevalence= 38%
Sensitivity = 75%
Specificity = 100%
PV + = 100%
PV - = 87%
Specificity & Predictive Value
Surgical biopsy
FNA
results
positive
Cancer No
Cancer
Total
41 5 46
negative 3 65 68
Total 44 70 114
16.
17.
18.
19. Decide whether to order ESR or directly MRI?
• A 57 yr old man presents with h/o aching low back pain that
persists at rest and is worse by bending and lifting.
Progressively getting worse in last 6 wks-awakening him at
night.
• Within past 10 days he has noticed numbness in Rt buttock
and thigh and weakness in Rt lower limb.
• He had no fever but has lost 10 lb Wt. in last 4 months.
• O/E – Temp. is 99.6F, tenderness in the lower lumber spine,
decrease in sensation over dorso-lateral aspect of Rt. foot,
weakness in Rt ankle aversion. Deep tendon reflexes normal
• ! You suspect that man has 20% chance of spinal malignancy
• ESR ≥20 mm/h has 78% sensitivity & 67% specificity
• MRI has 95% sensitivity AND 95% specificity!!
• Suppose we have 1000 patients
20. We can use any of he following methods
• 2 X 2 Table Method
• Likelihood Ratio (gives odds)
• Decision Tree method And
• Bayes Theoram
Don’t
Tt
Test Treat
Do
n’t
Tt
Test Treat
Don’t
Tt
Test Treat
No difference
Test is quite accurate
with little Risk
Test is of low accuracy
or Risky
21. How will the prior probability of 20% change with +ve ESR?
Disease
Test (ESR) D+ D-
T+ (TP) 156 (FP) 264 420
T- (FN) 44 (TN) 536 580
200 800 1000
Predictive Value of a Positive test PPV (PV+) = 156/420 = 0.37
Increased from 20% to 37%
Predictive Value of a Negative test NPV = 536/580 = 0.92
A) - What is the probability that the patient doesn’t have the Dis. though the test is +ve (FP)?
B)- What is the probability that the patient does have the disease though the test is –ve (FN)?
A) - 264/420 = 0.63 (hence minimal use as screening test), and B)- 44/580 = 0.08
22. MRI has 95% sensitivity AND 95% specificity
And will have PVs as follows:-
Disease
Test (MRI) D+ D-
T+ (TP) 351.5 (FP) 31.5 383
T- (FN) 18.5 (TN) 598.5 617
370 630 1000
Predictive Value of a Positive test PPV (PV+) = 351.5/383 = 0.918
Predictive Value of a Negative test NPV (NPV) = 598.5/617= 0.970
23. Likelihood Ratio
LR = Chance of picking the Dis. out of total Diseased
Chance of picking the Dis. out of total Dis. Free
= sensitivity/ 1-specificity (FN)
= LR = 0.78/ 1-0.67 = 0.78/0.33 = 2.36
(In case of ESR where sensitivity = 78% & Specificity = 67%);
Pre Test odds = Prior Probability
1- Prior Probability
Post Test odds = LR X Pre test odds = 0.78 X 0.2
0.33 X 0.8
= 2.36 X 0.25 = 0.59
Posterior probability (PPV) = post test odds/ 1+ post test odds
= 0.59/ 1+ 0.59 = 0.37 = 37%
= 0.20/1- 0.2 = 0.25
=0.156/ 0.264
24. Reliability or Repeatability of a Test
• Factors responsible for variation in the results:
1. Intra subject (within the individual) variation
2. Intra observer variation (variation in the
reading of test result by the same observer)-
greater the subjective element in the reading
more is this error
3. Inter observer variation (variation in the
reading of test result between observers)
25. Inter observer Variation
Reading No. 1
Reading No. 2 Abnormal Suspect Doubtful Normal
Abnormal A B C D
Suspect E F G H
Doubtful I J K L
Normal M N O P
Percent Agreement =
A + F + K + P
Total readings
X 100
27. Kappa Statistics
• The extent to which two observers (physician/
nurse/ radiologist etc) agree is an important
Index of good quality of care
• Yet, there is a fraction based ‘solely on chance’
for agreement between two observers
• What we want to know is – to what extent
did the education/ training that the observers
received improve the quality of their
observation (how much increased percent
agreement between them beyond chance! )
28. Rationale of the kappa statistics
• First we want to know – how much better is the
agreement between the observers’ readings than
would be expected by chance
= (% agreement observed - % agreement expected
by chance alone)
• What is the maximum improvement the
observers can have than expected by chance
100% - % agreement expected by chance alone
• Kappa expresses the extent to which the observed
agreement exceeds chance agreement relative to
maximum that the observer can hope to improve
29. • Kappa =
[Percent Agreement
Observed]
[Percent Agreement
expected by chance alone]
-
[Percent Agreement
expected by chance alone]
100% -
Landis and Koch suggested that :-
kappa greater than 0.75 = excellent agreement
Kappa of 0.40 to 0.75 = intermediate to good agreement
33. Exercise
• PA was used to screen Br. Ca. in 2,500 women
with biopsy proven adenocarcinoma and in
5,000 age matched control wome. The result
of PA were +ve in 1800 cases and 800 control.
• What is the sensitivity, specificity and PPV of
PA ?
• 72%, 84% and 69%
34. • A screening test is used in the same way in two
similar Pop. But the proportion of FPs among those
who test +ve in Pop. A is lower than that among
those who test +ve in Pop. B
• What is likely explanation for this finding ?
• Prevalence of disease is higher in Pop. A
• Compare PA and Audiometry test for hearing
problem using sen.itivity and specificity ?
PA
Test
Hearing Prob.
D+ D-
T+ 240 40
T- 60 160
Audiometry
Test
Hearing Prob.
D+ D-
T+ 240 40
T- 60 160
More sensitive and less specific
35. • Two Pead. Test for streptococcal infection one
(X) using standard culture test which is 90%
Sen. And 96% Sp. While other (Y) uses New
culture test which is 96% Sen. And 96% Sp.
• If 200 patients undergo culture with both tests
which is correct:-
a) X will correctly identify more people
b) X will correctly identify fewer people
c) X will correctly identify more people without infection
d) The Prev. of Strep. Inf. Is needed to know who will
correctly identify more people
e) Ans is b
36. • In a screening for colon Ca. 50-75 yrs old were
screened with Hemoccult test.
• If Hemoccult test has 70% Sen. & 75% Sp. And
Prev. of Ca. colon is 12/1000, what is the PPV
• 3.13%
• If Hemoccult test is –ve no further testing is
done but if its +ve Hemoccult test II is done .
• If this second test is also +ve for blood in stool,
more extensive tests are done. What is the
effect on Net Sen. & Sp. of this method?
• Net Sen. Is decreased and Net Sp. Increased
37. • Two physicians were asked to classify X-rays
abnormal or normal independently.
Physician 2
Physician 1 Abnormal Normal Total
Abnormal 40 20 60
Normal 10 30 40
Total 50 50 100
1. What is the simple % agreement between the two physician - …………..
2. The % agreement between the two physician, excluding the X-rays that bot
classified as normal is ………………..
3. The value of kappa is ………….
4. How will you rate this kappa ………….
52. The process
of making
an objective
and
systematic
analysis of
information
from all the
randomized
controlled
trials
Editor's Notes
In a perfect world medical test would always be correct +ve test will mean disease and –Ve test will mean ‘no disease’ but in actuality that is not the case!!!!
Internal Validity – the extent to which the results reflect the true situation.
To improve on it :-
Restricting the type of subjects (Inclusion/Exclusion Criteria)
The environment in which the study is performed
External Validity – Generalizability (sample size!)
The greater the sensitivity of a test, more likely the test will detect the disease. For FNA 93% of all breast cancer patients had positive results Negative result with test having High Sensitivity would virtually exclude the possibility that patient has the Disease
The greater the specificity of a test, the more likely it is that persons without the disease will be excluded from the consideration of having the disease
Patient Profile extended – 114 such patients were tested with both biopsy and FNA test
PPV-? – 15.6% to 63%
If we do not want False Positives – two stage testing
If we do not want False Negatives – Simultaneous testing
A decision must be reached on whether to order ESR or proceed directly with lumber MRI. It depends on –
prior probability of Spinal Malignancy
the accuracy of ESR in detecting malignancy among who have it (sensitivity)
its ability to label a person not having disease among disease free people (specificity)
Application of probabilistic and statistical principles to individual patient is evidence based medicine
evaluating new diagnostic procedures
determining most cost effective approach
evaluating available Tt options
A physician’s best guess (index of suspicion that pt has the disease – prior probability) depends on knowledge of prev. and is revised upwards or downwards depending up on S/S and other characteristics like race/ age/ sex etc
Decision to do test &/ or Tt depends on the risk of the Diagnostic test, the benefits of Tt to patient, the risk of Tt to patient with and without disease and the accuracy of the Test.
If we ask two roadside persons to mark a set of X-rays as positive and negative indepently there will be some agreement between their readings just by chance
Kappa statistics proposed by Cohen in 1960
The ROC plot of a given test is obtained by calculating the sensitivity and specificity of every observed value, and then plotting sensitivity (on the Y axis) against 1 - specificity (on the X axis). A test that does not discriminate between normal and abnormal would give a diagonal straight line from the bottom left corner to the top right corner. All points on such a line represent a 1:1 ratio of true to false positives. An ideal test would give a rectangular plot passing from the origin at the bottom left hand corner towards top left hand corner at first and thence to the top right hand corner. In reality the ROC curves of many of the tests in common use fall in between these extremes. The cut-off point for deciding between normal and abnormal is selected arbitrarily where the ROC curve changes direction from being vertical to horizontal. The more the ROC curve arches into the upper left hand corner away from the diagonal, the better the test.
The overall odds ratio is then calculated by pooling the data of all the studies. This is also called "typical" odds ratio. It is calculated by the difference between number of deaths in the treatment group (i.e. the number observed) and the number of deaths in this group if the treatment were ineffective (i.e. number expected). This gives the Observed minus the Expected statistic. The confidence interval of O E is also calculated
The outcome in the case of each study can be estimated separately by calculating the O E value. If the observed number (O) differs systematically from the expected number (E), there is clear evidence of effect.
The totaled O E gives a measure of the overall statistical significance and the effect size