Comparing Survival Extrapolation within All-Cause and Relative Survival Frameworks by Standard Parametric Models and Flexible Parametric Spline Models Using the Swedish Cancer Registry.

BACKGROUND: In health technology assessment, restricted mean survival time and life expectancy are commonly evaluated. Parametric models are typically used for extrapolation. Spline models using a relative survival framework have been shown to estimate life expectancy of cancer patients more reliably; however, more research is needed to assess spline models using an all-cause survival framework and standard parametric models using a relative survival framework. AIM: To assess survival extrapolation using standard parametric models and spline models within relative survival and all-cause survival frameworks. METHODS: From the Swedish Cancer Registry, we identified patients diagnosed with 5 types of cancer (colon, breast, melanoma, prostate, and chronic myeloid leukemia) between 1981 and 1990 with follow-up until 2020. Patients were categorized into 15 cancer cohorts by cancer and age group (18-59, 60-69, and 70-99 y). We right-censored the follow-up at 2, 3, 5, and 10 y and fitted the parametric models within an all-cause and a relative survival framework to extrapolate to 10 y and lifetime in comparison with the observed Kaplan-Meier survival estimates. All cohorts were modeled with 6 standard parametric models (exponential, Weibull, Gompertz, log-logistic, log-normal, and generalized gamma) and 3 spline models (on hazard, odds, and normal scales). RESULTS: For predicting 10-y survival, spline models generally performed better than standard parametric models. However, using an all-cause or a relative survival framework did not show any distinct difference. For lifetime survival, extrapolating from a relative survival framework agreed better with the observed survival, particularly using spline models. CONCLUSIONS: For extrapolation to 10 y, we recommend spline models. For extrapolation to lifetime, we suggest extrapolating in a relative survival framework, especially using spline models. HIGHLIGHTS: For survival extrapolation to 10 y, spline models generally performed better than standard parametric models did. However, using an all-cause or a relative survival framework showed no distinct difference under the same parametric model.Survival extrapolation to lifetime within a relative survival framework agreed well with the observed data, especially using spline models.Extrapolating parametric models within an all-cause survival framework may overestimate survival proportions at lifetime; models for the relative survival approach may underestimate instead.

Survival in Swedish patients with systemic sclerosis: a nationwide population-based matched cohort study.

OBJECTIVES: To conduct the first-ever nationwide, population-based cohort study investigating survival patterns of all patients with incident SSc in Sweden compared with matched individuals from the Swedish general population. METHODS: We used the National Patient Register to identify patients with incident SSc diagnosed between 2004 and 2015 and the Total Population Register to identify comparators (1:5), matched on sex, birth year and residential area. We followed them until death, emigration or the end of 2016. Follow-up of the general population comparators started the same date as their matched patients were included. We estimated all-cause survival using the Kaplan-Meier method, crude mortality rates and hazard ratios (HRs) using flexible parametric models. RESULTS: We identified 1139 incident patients with SSc and 5613 matched comparators. The median follow-up was 5.0 years in patients with SSc and 6.0 years for their comparators. During follow-up, 268 deaths occurred in patients with SSc and 554 in their comparators. The 5-year survival was 79.8% and the 10-year survival was 67.7% among patients with SSc vs 92.9% and 84.8%, respectively, for the comparators (P < 0.0001). The mortality rate in patients with SSc was 42.1 per 1000 person-years and 15.8 per 1000 person-years in their comparators, corresponding to an HR of 3.7 (95% CI 2.9, 4.7) at the end of the first year of follow-up and 2.0 (95% CI 1.4, 2.8) at the end of the follow-up period. CONCLUSION: Despite advances in understanding the disease and in diagnostic methods over the past decades, survival is still severely impacted in Swedish patients diagnosed with SSc between 2004 and 2015.