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Overview and Objectives

Changes in Life Expectation for Diffuse Large B-Cell Lymphoma (DLBCL) Patients, 1983 – 2014 results from analysis of US SEER data Ron Dewar, Registry and Analytics, Nova Scotia Health Authority (Canada) Nadia Howlader , Angela Mariotto , National Cancer Institute (USA)

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Overview and Objectives

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  1. Changes in Life Expectation for Diffuse Large B-Cell Lymphoma (DLBCL) Patients, 1983 – 2014 results from analysis of US SEER data Ron Dewar, Registry and Analytics,Nova Scotia Health Authority (Canada) Nadia Howlader, Angela Mariotto,National Cancer Institute (USA) Presented to the joint NAACCR / IACR meeting, June 2019

  2. Overview and Objectives • Diffuse Large B-Cell Lymphoma (DLBCL) • Introduce concept of expectation of life • Expectation of life for general population • Expectation of life for cancer patient population • Results and their interpretation • Data sources • SSA projections • SEER*Stat (9 SEER registries 1983 – 2014)

  3. Diffuse Large B-Cell Lymphoma (DLBCL) • B-Cell Lymphomas > 90% of all Non-Hodgkin Lymphoma (SEER 9, 2016) • DLBCL ~23% of all B-Cell Lymphoma incidence, ~1/3 of NHL deaths • Recent decline in incidence (since 2004) and mortality (since 1998) • Improvements in 5-yr survival possibly due introduction of targeted therapies (rituximab) to standard (CHOP) • Consider the impact of this disease on the future life expectancy of DLBCL patients in US

  4. Expectation of Life • Total years lived (or projected to live) by all members of a cohort, divided by the initial cohort size • General population life expectation is published regularly, based on current (or projected) mortality rates • Commonly expressed as ‘life expectancy at birth’, but can be computed from any age starting point (‘residual life expectancy’) • Corresponding calculation for cancer patients?

  5. Expectation of Life: All Cause Mortality and Proportion Surviving, US women, 2014 Proportion alive (survival curve) Mortality rate (all causes)

  6. Calculation of expectation of life, cancer patients • Extrapolate patient all causes (observed) survival • Evaluation by T. Andersson (2012) suggests: • Model, then extrapolate relative survival (AKA excess hazard) stable for many sites after 7 – 10 years • Calculate observed survival using expected survival estimate, since • RS = OS/expected, then • OS = RS * expected • Numerical integration of extrapolated OScurve • Data sourcesSEER 9, Nov 2016 dataset, ~ 32,000 DLBCL patients (1983 – 2014) covariates: age in years survival time in months sex Ann Arbor Lymphoma (1983+) Stagecomplete life tables for US (1970 – 2015) (from SEER*Stat)Life Tables for the United States Social Security Area (1900-2100)https://www.ssa.gov/oact/NOTES/pdf_studies/study120.pdf

  7. Loss in expectation of life • Difference between population expectation and expectation for cancer patients • Compute at the individual or summed over all individuals to obtain a population level measure of disease burden • Express as loss in expectation of life (LEL) in years proportion (%) of future life years lost • Possible interpretations population burden of cancer (total years lost) change over time as measure of progressimpact of covariate distribution impact on individual with specific covariates (age, sex, stage, …)

  8. Expectation of Life, Women in US, 2015 at age 55showing Loss in Expectation of Life (LEL)

  9. Trends in Life Expectancy for DLBCL patients US SEER data (1983 – 2014)

  10. DLBCL Life Expectancy by age and sex, 1983 - 2014 8.4years

  11. Loss of Life Expectancy (%) by age and sex, DLBCL 1983 - 2014 27.5%

  12. Trends in Life Expectancy* for DLBCL patients by Ann Arbor (1983+) Lymphoma stage *Age standardised to 2014 age distribution

  13. Loss Life Expectancy* (%) for DLBCL patients by Ann Arbor (1983+) Lymphoma stage *Age standardised to 2014 age distribution

  14. Recent advances in survival from DLBCL can be seen in the US SEER data across all ages and stage groups (1983 – 2014 data) • Disease burden (age standardised % Loss in Life Expectancy) is now similar for Ann Arbor (1983+) Stage I and II at 25% for both men and women • Loss in Expectation of Life can be seen as an adjunct to survival estimates and may improve communication patient – physician interaction managers and planners of the cancer system • Caveats: need a wider conversation around uses, interpretation availability of projected life tables (ideal, but not entirely necessary) sensitivity to modeling choices should be evaluated and reported stage-specific trends subject to same caveats as survival trends • Conclusions

  15. Thanks to: • Nova Scotia Health Authority, Cancer Care Program • National Cancer Institute • SEER*Stat • Dr. Paul Lambert, Dr. Therese Andersson (authors of Stata routines)

  16. Any questions?

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