NY Prostate Cancer Conference - J. Bellmunt - Panel discussion D: Do we need better predictive models in advanced prostate cancer?
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This document discusses several predictive models and nomograms for prostate cancer outcomes: - The CAPRA nomogram predicts outcomes after radical prostatectomy using clinical factors. - The J-CAPRA nomogram was designed for patients receiving primary androgen deprivation therapy and predicts cancer progression and mortality. - Nomograms have been developed to predict survival for patients with metastatic castration-resistant prostate cancer using PSA kinetics and other clinical variables. - Additional nomograms aim to predict outcomes after specific therapies like docetaxel or abiraterone. Prospective validation of these tools is still needed to help guide treatment decisions.
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NY Prostate Cancer Conference - J. Bellmunt - Panel discussion D: Do we need better predictive models in advanced prostate cancer?
- 1. April 7-9, 2011 Memorial Sloan-Kettering Cancer Center New York, US
- 2. Nomograms currently represent one of the most accurate and discriminating tools for predicting outcomes in patients with Pca Despite limitations, predictive tools can provide individualized, evidence-based estimates for a number of PCa endpoints, thereby helping in the complex decision-making process. Predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives There are no prospective randomized studies that clearly demonstrate that the use of prediction tools improve patient care or reduce patient anxiety, decisional conflict, or regret PREDICTIVE TOOLS AND NOMOGRAMS
- 3. PREDICTING MODELS FOR ADVANCED HSPC
- 4. Three polymorphisms in separate genes ( CYP19A1, HSD3B1, and HSD17B4) were significantly ( P .01) associated with time to progression (TTP) during ADT,
- 7. CAPRA (Cancer of the Prostate Risk Assessment ) Predict pathological and biochemical outcomes after radical prostatectomy, predict metastases, predict prostate cancer–specific mortality, and all-cause mortality. CAPRA scores were calculated at diagnosis from the PSA level, Gleason score, percentage of biopsy cores that were positive for cancer, clinical tumor stage, and age at diagnosis. Each single-point increase in the CAPRA score was associated with increased bone metastases cancer-specific mortality and all-cause mortality. Patients with clinically localized prostate cancer who were managed with one of five primary modalities, the CAPRA score predicted clinical prostate cancer endpoints with good accuracy
- 8. The first instrument that uses information available at time of diagnosis to predict accurately the development of metastases, cancer-specific mortality, and all-cause mortality, irrespective of primary treatment
- 9. Comparison of risk features between large disease registries from the United States and Japan, aiming to build and validate a risk prediction model applicable to primar androgen deprivation therapy (PADT ) patients. Risk Assessment [J-CAPRA]) was designed and validated to be specifically applicable to PADT patients, and more relevant to high-risk patients than existing instruments J-CAPRA—scored 0 to 12 based on Gleason score, PSA level, and clinical stage—predicts progression-free survival among PADT patients in J-CaP with a c-index of 0.71, and cancer-specific survival among PADT patients in CaPSURE with a c-index of 0.84. Applicable to those with both localized and advanced disease, and performs well in diverse populations
- 10. A PSA of 4 ng/mL or less after 7 months of AD is a strong predictor of survival.
- 11. PSA-P, defined as an increase of 25% greater than the nadir and an absolute increase of at least 2 or 5 ng/mL, predicts OS in HSPC and CRPC and may be a suitable end point for phase II studies in these settings.
- 12. PREDICTING MODELING FOR ADVANCED CRPC
- 14. Halabi et al., JCO 21:1232-7, 2003 Useful to predict individual survival probabilities and to stratify metastatic HRPC patients in randomized phase III trials
- 18. Something new after 2008 ?
- 19. Nomogram Development PSADT has emerged as an easily obtainable and clinically relevant prognostic marker in several stages of prostate cancer,including pre-prostatectomy, pre-radiation therapy, rising PSA after local therapy, nonmetastatic CRPC, and... -------- in metastatic CRPC
- 20. Survival by PSADT 0.25 0.50 0.75 1.00 Survival (%) 0 5 10 15 20 25 30 35 40 45 50 Survival (months) PSADT <1 month PSADT 1–2 months Log-rank p<0.001 0 Eisenberger M, et al. J Clin Oncol 2007; 25: abstract # 5058 & PSADT is an Independent Risk Factor for Death in HRPC PSADT 4–6 months PSADT >6 months PSADT 2–3 months
- 21. Purpose: To develop a prognostic model and nomogram using baseline clinical variables to predict death among men with metastatic hormone-refractory prostate cancer (HRPC)
- 22. Nomogram for predicting 1-, 2-, and 5-year survival (HRPC) incorporating PSA kinetics
- 23. Nomograms provide the clinician with an overall assessment of a patient’s prognosis, but do not directly impact on decisions for the ideal starting point for docetaxel-based therapy, given that all patients in these nomograms had received therapy Additional factors are also likely to contribute to OS (covered in other nomograms,) - LDH and albumin, serum biomarkers for vascular endothelial growth factor and other cytokines, CTCs, and other unmeasured prognostic factors.
- 25. Simple ways to predict survival
- 26. They analyzed predictors of postprogression survival according to both prechemotherapy and postchemotherapy variables with adjustment for potential confounders. The nomogram may also improve the information delivered to men with CRPC about prognosis. The prognostic factors identified in this study include both known prechemotherapy factors and type of progression and duration of chemotherapy. Predicting post chemo survival
- 28. They investigated pre-treatment factors that predicted a > 30% PSA decline (30% PSAD) within 3 months of starting chemotherapy, Assessed performance of a risk group classification in predicting PSA declines and overall survival (OS) in men with mCRPC. Four independent risk factors predicted 30% PSAD: pain, visceral metastases, anemia and bone scan progression. Risk groups (good: 0–1 factors, intermediate: 2 factors and poor: 3–4 factors) were developed may facilitate evaluation of new systemic regimens warranting definitive testing in comparison with docetaxel and prednisone
- 29. Kaplan–Meier estimates of overall survival according to risk group classification. Median survival figures are represented in the legend
- 30. Normalization of ALP remained prognostic for OS after adjusting for PSA decline > 30% by day 90 (HR 0.79, 95% CI 0.65– 0.97, P 0.022).
- 31. In patients with CRPC, the association of measurable tumor responses with overall survival (OS) is unknown Four hundred twelve patients enrolled on the TAX327 trial had measurable tumors (CR/PR, 9.0%) PRs demonstrated longer median OS (29.0 months) than patients with SD (22.1 months) or those with PD (10.8 months) or those who were not assessed (12.7 months) Radiologic response remained a significant but modest post-treatment prognostic factor for OS after adjusting for treatment, pain response, and 30% PSA decline (P = .009)
Editor's Notes
- 10 627 men with clinically localized prostate cancer, who underwent primary radical prostatectomy, radiation therapy (external beam or interstitial), androgen deprivation monotherapy, or watchful waiting/active surveillance, and had at least 6 months of follow-up after treatment.
- The ability of the new instrument, designated the Japan Cancer of the Prostate Risk Assessment (J-CAPRA) score, to predict clinical progression-free survival (PFS) was assessed with Kaplan-Meier analysis, Cox proportional hazards regression, and calculation of Harrell’s c-index.
- For phase III trials, the stratification of patients ensures that the treatment groups are balanced with respect to the known or possible factors to avoid the possibility of confounding. Furthermore, the utility of risk stratification may help identify subsets of patients that may have prolonged survival duration. Indeed, it is possible that some treatment will be beneficial for only a subgroup of patients but not for others.
- have not been shown conclusively to be an independent prognostic factor in HRPC (retrospective reviews, small size)
- The most significant predictors of mortality in the HRPC database are the presence of liver metastases , number of metastatic sites , and clinically significant pain (present pain inventory (PPI) >2 and/or an analgesic score (AS) > 10) (data not included in previous nomograms)
- The importance of a prognostic model rests on its ability to capture clinically relevant and measurable variables for routine use by clinicians to inform patients, improve palliation and treatment decisions, and create homogeneous prognostic strata for randomized comparative trials of therapeutic agents. may be useful for clinical prognostication or stratification of subjects in clinical trials in this population. Prospective external validation of this model is planned and will be essential for more widespread clinical application.
- The prognostic ability of this classification remains modest, and thus this classification should not be used to guide therapy nor to judge the survival benefit of docetaxel chemotherapy
- Retrospective studies of the Southwest Oncology Group (SWOG)-9916 and the TAX327 trials, which compared docetaxel-based with mitoxantrone-based chemotherapy, demonstrated that a prostate-specific antigen (PSA) decline 30% or 50% within 3months had a moderate degree of surrogacy for extended overall survival (OS) in the setting of cytotoxic chemotherapy.3,4 Retrospective analyses of these trials have also demonstrated that an increase in PSA at 3 months correlates with poor overall survival (OS).5,6 A recent retrospective study demonstrated that progression-free survival (PFS), defined by a composite endpoint (progression by bone scan, PSA criteria by PSA working group, and measurable tumor progression), also correlates with poorer OS.7
- Porter et al. developed a tool for prediction of cause-specific survival in patients exposed to hormonal therapy after RP failure (n=114) [89]. The internally validated discrimination of the tool was only 66%. Among the three prediction tools for AIPC patients, those of Smaletz et al [90] and of Halabi et al [91] were developed and externally validated in heavily pretreated patients, who had been exposed to one to several experimental agents. In external validation, the accuracy of the prediction tool of Smaletz et al. was 67% and that of Halabi et al. was 67% and 68%. Svatek et al. devised a contemporary prediction tool using a population with a median survival of 52 months who had not received experimental therapies. This prediction tool relies predominantly on PSA doubling time and PSA level at hormone therapy initiation. Internal validation of this prediction tool yielded a discrimination of 81%. The contemporaneity and homogeneity of the patient population make this prediction tool very attractive when survival needs to be assessed in patients with AIPC.