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Survival Estimates in Sickle Cell Anemia: Assessing Health and Mortality Rates

This article discusses the relevance of survival information in counseling and medical management of sickle cell anemia. It explores the challenges in obtaining appropriate samples and the biases that may affect survival estimates. The study conducted in Jamaica reveals the high early-life mortality and the survival rates of patients diagnosed with sickle cell anemia. Different statistical techniques and adjustments are discussed to compensate for biases and estimate lifetime survival accurately.

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Survival Estimates in Sickle Cell Anemia: Assessing Health and Mortality Rates

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  1. Survival estimates in prevalent cohorts: an application in sickle cell anemia Authors: KJJ Wierenga, IR Hambleton, NA Lewis Address: Sickle Cell Unit, TMRI, University of the West Indies, Mona, Kingston7, Jamaica, West Indies Correspondence please to: Klaas JJ Wierenga or Ian R Hambleton Original article is freely available on the Lancet website

  2. Relevance of survival information Counseling Assessment of medical management Targeting clinical research Definition of health-status

  3. Difficulty in obtaining appropriate sample • Unbiased estimation of lifetime survival requires: • Patient identification at birth • Prospective follow-up thereafter • Neonatal screening began in 1970s for sickle cell anemia: • Neonatal cohorts are available • Not old enough for lifetime survival estimates

  4. Use of an alternative sample • Clinic-ascertained patients offer an alternative population • These populations have documented biases • To minimize the effect of these biases we must consider • Data quality • Statistical methods

  5. Late-entry bias (1) • Entry to clinic after disease onset • Quantified by period between onset and arrival • Non-arrival to clinic is indefinite late-entry bias • Not requiring clinic intervention • Death before attending clinic

  6. Late-entry bias (2) Mortality in SCA increased in early life Peaks between 6 months and 3 years Missing deaths can impact on survival if mortality rates for patients in and out of a study differ Data analysis techniques to compensate for this bias should be applied

  7. Default bias Attending patients might subsequently default Bias introduced if reason for default related to disease Minimize default during data collection Further consideration during analysis

  8. Sickle cell anemia in Jamaica Most common form of sickle cell disease in Jamaica Allele frequency is 0.055 3 cases per 1000 live births High early-life mortality Many patients survive into 4th or 5th decade

  9. The survival study of SCA Patients diagnosed with SCA Attended study centers between Jan 1987 and Dec 1996

  10. Protecting against default-bias 1007 defaulting patients and 975 of these were traced. Final status of patients:

  11. 1 .75 .5 .25 0 0 10 20 30 Late-entry bias Late-entry exists: Age (years)

  12. Adjusting for late-entry bias (statistical adjustment) Generic statistical adjustment available Method Decreases at-risk population Assumption Mortality rates in / out of clinic are the same

  13. Survival (using statistical adjustment) 1 men women .75 .5 .25 0 0 20 40 60 80 0 20 40 60 80

  14. A reminder Assumption: Mortality rates in and out of the clinic are the same

  15. Mortality rates 12 8 Mortality (100 patient years) 4 0 10 20 30 40 50 Age (years)

  16. Mortality rates 12 8 Mortality (100 patient years) 4 0 10 20 30 40 50 Age (years)

  17. Mortality rates 12 8 Mortality (100 patient years) A 4 C 0 10 20 30 40 50 Age (years)

  18. Mortality rates 12 8 Mortality (100 patient years) 4 0 10 20 30 40 50 Age (years)

  19. Mortality rates 12 8 Mortality (100 patient years) 4 0 10 20 30 40 50 Age (years)

  20. Conclusion The assumption that mortality rates in and out of the clinic are the same does not apply in this case!

  21. Adjusting for late-entry bias (simulation adjustment) • Using JCS to simulate ‘true’ mortality • Method Simulate the proportion of ‘excess’ cohort deaths in the clinic population • AssumptionCohort mortality will not exceed clinic-based mortality beyond early adulthood

  22. Mortality rates 12 8 Mortality (100 patient years) 4 0 10 20 30 40 50 Age (years)

  23. 1.00 0.75 0.50 0.25 0.00 0 20 40 60 80 0 20 40 60 80 Survival (using simulation adjustment) men women

  24. Discussion – Jamaica vs. US The second and largest study on SCA survival The first estimates of uncertainty surrounding SCA survival Demographics are similar to USage at entrylength of follow-up Median survival is similar to the USmen: US 42 years, Jamaica 43 years (40-49)women: US 48 years, Jamaica 47 years (38-55)

  25. Discussion - Simulation • Higher than statistical adjustment men: 10 years higher women: 11 years higher • Lower than 1991 Jamaican survival men: 14 to 22 years lower women: 8 to 21 years lower

  26. Summary • Use of unselected cohorts not (yet) possible to examine life-time survival in SCA • Survival summaries depend on assumptions made and techniques used.

  27. Remember • Lifetime survival only basic summary of disease expression • Allows standard comparison across diseases • Use of clinical and patient-centered measures more sensitive

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