1 / 41

Aging, Frailty, and Medical Therapy for Colorectal Cancer: Who Should Be Treated and How?

Aging, Frailty, and Medical Therapy for Colorectal Cancer: Who Should Be Treated and How?. Martine Extermann M.D., Ph.D. Moffit Cancer Center Daniel Sargent Ph.D. Mayo Clinic Cancer Center Richard M. Goldberg M.D. University of North Carolina Lineberger Comprehensive Cancer Center.

badrani
Download Presentation

Aging, Frailty, and Medical Therapy for Colorectal Cancer: Who Should Be Treated and How?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Aging, Frailty, and Medical Therapy for Colorectal Cancer: Who Should Be Treated and How? Martine Extermann M.D., Ph.D. Moffit Cancer Center Daniel Sargent Ph.D. Mayo Clinic Cancer Center Richard M. Goldberg M.D. University of North Carolina Lineberger Comprehensive Cancer Center

  2. Elderly and/ or frail patients with colorectal cancer - a clinician's approach Richard M. Goldberg University of North Carolina Lineberger Comprehensive Cancer Center

  3. Disclosures: Consulting and/or Research Support • Abbott • Amgen • Astra Zeneca • BMS • Enzon • Genentech • GHI • ImClone • Myriad • NCI • Poniard • sanofi-aventis

  4. Statistics • 2/3 of pts with mCRC are >65 years old • 40% > 75 years old Edwards , Cancer 94: 2766-92, 2002 And http:seer.cancer.gov

  5. Additional Expected Years of Life By Age/Gender Kohne, Oncologist , 13:390, 2008

  6. Colon Cancer Stage II vs Stage III Recurrence Rate by 6 mo intervals Stage 2: 67% of recurrences occur by 3 years Stage 3: 75% of recurrences occur by 3 years Sargent, JCO 2005

  7. 100 80 60 3 Year DFS p-value = 0.318 40 Control 20 Experimental 0 39 44 48 51 54 55 58 60 62 64 66 68 70 73 74 (n=547) (n=547) (n=509) (n=509) (n=584) (n=584) (n=606) (n=606) (n=556) (n=556) (n=544) (n=544) (n=523) (n=523) (n=633) (n=633) (n=512) (n=512) (n=518) (n=518) (n=513) (n=513) (n=503) (n=503) (n=543) (n=543) (n=502) (n=502) (n=338) (n=338) Subpopulations by Median Age STEPP analysis – Oxaliplatin-based therapyage cutoff validation for observed lack of added treatment effect Age 68.5 Age 70

  8. A Five Part Talk • Surgery • Radiation • A few relevant chemotherapy/biologic reports • Comparative effectiveness research • Clinical approaches

  9. Percent of Patients Who Died Related to Colorectal Cancer Surgery • 6457 Dutch patients • 4.4 % overall mortality, 10% and 13% if >80 Damhuis, Int J ColorectDis, 11:45-48,1996

  10. Colorectal Cancer Surgery in England:Laparoscopic surgery may be better • 29,000 patients > 75 years old operated from 1996-2007 at National Health Service Hospitals • Hospital Episodes Database • Emergency procedures excluded • 865 laparoscopic procedures • 12% in 2007 • Postoperative mortality 3.1% • 5.4% for open colectomy, p=0.003 • Range between hospitals 0-14.1% Faiz, Colorectal Dis, epub April 19,2010

  11. Liver Resection In >70 Year Old Patients • 1624/7764 (21%) Patients operated on at LiverMetSurvey Registry Centers in Europe were >70 • 70-74: 999 (13%) • 74-80: 468 (6%) • >80: 157 (2%) • 6% were over 70 in 1990, 26% in 2007 Adam, Br J Surg 97:366-76, 2010

  12. Liver Resection In >70 Year Old Patients • 1624/7764 (21%) Patients operated on at LiverMetSurvey Registry Centers in Europe were >70 • 70-74: 999 (13%) • 74-80: 468 (6%) • >80: 157 (2%) • 6% were over 70 in 1990, 26% in 2007 Adam, Br J Surg 97:366-76, 2010

  13. Outcomes: > 70 versus <70 years old • 60 day perioperative mortality p< 0.001 • 3.8% versus 1.6% • 60 day perioperative morbidity • 32% versus 29% • 3-Year overall survival 57% vs 60% p <0.001 • Median overall survival • 43 months versus 47 months

  14. 5-Year Overall Survival

  15. Liver Resection In >70 Year Old Patients • Preoperative Chemotherapy • No survival difference between those who did or did not have preoperative chemotherapy • Morbidity was higher 38% vs 32% p=0.03 • Postoperative chemotherapy • An independent predictor of survival HR 1.79, p <0.001

  16. Radiation for Rectal Cancer • Meta-analysis of 22 randomized trials of surgery +/- RT • Preop: 6350 patients in 14 trials • Postop: 2157 patients in 8 trials Colorectal Cancer Collaborative Group, Lancet 356:968-74, 2000.

  17. Rectal Cancer Meta-Analysis

  18. Age and Death Rates:Rectal Cancer and “Other”

  19. Dutch TME Trial Elderly Analysis • All patients received a total mesorectal excision • All patients given RT received 5 fractions of 500 cGy preoperatively • 1356 patients • 17% older than age 75 Rutten, Eur J Cancer, 43: 2295-3000, 2007

  20. TME Study Statistics

  21. Outcomes By Age and Study Arm

  22. Conclusions • Older patients benefit from RT + surgery more than younger patients • Older patients have a significantly higher complication and early death rate • Patients should be in optimal shape before surgery • If life expectancy exceeds 1 year combined modality therapy is best in the older patient

  23. Bevacizumab Pooled Analysis • Three 1st line and one 2nd line trial with 5-FU, irinotecan and oxaliplatin • 1,142/3007 (38%) > 65 years old • 24% > 70 years old Cassidy, J Cancer Res ClinOncol 136:737-43, 2010

  24. Overall Survival With and Without Bevacizumab

  25. Toxicity As a Function of Age

  26. Sources of Additional Data • Limited numbers of patients >75 are accrued to Phase II or III studies • These patients are carefully selected • There is only so much data out there • We need other sources of information

  27. Comparative Effectiveness Research

  28. Health Care Quality • IOM: • The degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge. • Underuse, overuse, misuse

  29. Outcomes – Comparative Effectiveness • Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care. • The purpose of CER is to assist consumers, clinicians, purchasers, and policy makers to make informed decisions that will improve health care at both the individual and population levels. (IOM, 2009)

  30. Federal Funding Mechanisms • AHRQ: • Agency for Health Research and Quality Quality • improvement and patient safety. • Outcomes and effectiveness of care. • Clinical practice and technology assessment. • Health care organization and delivery systems. • Primary care (including preventive services). • Health care costs and sources of payment.

  31. AHRQ Cancer Comparative Effectiveness • Medicare Modernization Act: • “…conduct research to improve the quality, effectiveness, and efficiency of Medicare, Medicaid, and State Children Health Insurance (SCHIP) programs.” • Increasing emphasis on patient-level attributes (rather than “the average patient”) that may modify the balance of benefits or harms can lead to more personalized medicine, reducing the pressure to try alternatives found to be ineffective in similar subgroups. • DEcIDE: Decisions about effectiveness research : • Expeditiously develop valid scientific evidence about the outcomes, comparative clinical effectiveness, safety, and appropriateness of health care items and services

  32. AHRQ Cancer DEcIDEComparative Effectiveness • Clinical trials • Relatively homogeneous population • Younger, healthier, more likely Caucasian • Randomization to control for unmeasured (and unmeasurable) heterogeneity • CER • Examinations prioritizing the context of heterogeneity • Better representativeness • Examination of subpopulations

  33. Examples Stage II/III Colorectal cancer Chemotherapy Trials • NEJM, 2004 • JCO, 2007 vs. SEER:

  34. Generalizable, results by sub-population NCDB study: n=86,000; hospitals=560(Jessup et al, JAMA, 2005)

  35. CER and Outcomes Research • CER has value, maximizing our understanding with observational data • Fast • Inexpensive • Can be very large databases • CER will not replace clinical trials • Larger future of outcomes research: Moving from studies of “what” to understanding “why”

  36. CER and Outcomes Research:Emerging Directions • Application of advanced methods using secondary data, including the development of new methods • AHRQ-sponsored White papers: • “Registries for Evaluating Patient Outcomes” • July 2009 DEcIDE RFTO (~$500,000 x 1 year): • “Methods to Study the Heterogeneity of Treatment Effects in Comparative Effectiveness Research” • Fall 2009: 10 x $10 million awards • Clinical and Health Outcomes Initiative in Comparative Effectiveness

  37. CER and Outcomes Research:Emerging Directions • Development and application of advanced data • Developing new data sources • Retrospective studies • Prospective studies • Fall 2009: $48 million • New Registries for CER • Data needs: • Sample size, generalizability of claims-based studies • Richness, depth of measures of survey / interview-based studies • Clinical detail, follow-up of registries

  38. Why new data and models?A prevailing model of cancer, comorbidity, and outcomes: • Current models are linear, simply specified, and fairly simple • Randomization controls for many relevant factors • Intent-to-treat is dominant Source: Geraci, JM, et al. (2005). “Comorbid Disease and Cancer: The Need for More Relevant Conceptual Models in Health Services Research.” Journal of Clinical Oncology. 23(30):7399-404.

  39. Why new data and models? • Because its just not that simple • We are increasingly interested in other outcomes, including Patient Reported Outcomes (PROS) • With observational data, you can’t randomize-out confounders and effect modifiers • Before we can make assumptions with them, we need to study them • Need new data that allow rich characterization of factors at multiple levels, with a substantial sample size for generalizability of findings and sub-population analysis

  40. What Data Sources Might We Use to Evaluate Effectiveness? • SEER-Medicare • NYSCR/CCR-Medicaid • CanCORS • NCCN • SEER • For purposes of anchoring comparison for overall mortality

  41. Conclusions • Elderly colorectal cancer patients are underrepresented in clinical trials • Surgery (including hepatic resections) and RT for rectal cancers can be done safely and effectively but leads to higher early death rates • CER can help answer some of the questions in this subpopulation

More Related