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Assessing the consistency of overall survival extrapolations in Swedish health technology assessment reports of oncology treatments using extended follow-up data.

Created on 26 Sep 2026

Authors

Máté Szilcz, Olof Mogard, Mattias Ekman, Olof Lindgren, Fredrik Nilsson, Kasper Johannesen, Emma Medin

Published in

Journal of medical economics. Volume 29. Issue 1. Pages 2406-2422. Epub Sep 26, 2026.

Abstract

Long-term overall survival (OS) extrapolations underpin cost-effectiveness appraisals, projecting survival beyond trial follow-up. We aimed to compare extrapolations presented in manufacturer submissions and appraisals published by the Swedish Dental and Pharmaceutical Benefits Agency (TLV) with extrapolations using OS data with longer follow-up available after the original appraisal.
We retrieved publicly available appraisals for oncology compounds from 2009 to 2019. For each appraisal, Kaplan-Meier curves of OS and base case extrapolation assumptions were collected. Longer-term OS data were identified through literature review and supplemented by manufacturers, then digitized to create pseudo-individual patient data. The extrapolation approach used in each appraisal was reapplied on the follow-up data cut to produce long-term OS predictions. Predictions from the original and follow-up data cuts were compared by area under the curves (AUC) and Akaike information criterion (AIC)-based ranking.
Forty reports were included. The average duration of the original data cut was 28.1 months. Using the follow-up data cut, with an average follow-up of 54.2 months, the average AUC of extrapolated OS estimates increased by 8.8% (95% CI 5.2% to 12.6%) under TLV assumptions and by 10.9% (95% CI 6.9% to 15.1%) under manufacturer assumptions. Thirteen (33%) TLV cases and 14 (35%) manufacturer cases showed AUC increases greater than 10%. In the AIC model-rank analysis, 18 models ranked worse when fitted to the longer-term data than to the original data, 16 ranked the same or better, and six were excluded.
Long-term survival estimates generally increased when original assumptions were applied to follow-up OS data, with material increases (>10%) in roughly one-third of cases, indicating original extrapolations were frequently conservative for the active arm. The findings support revisiting survival model fit, treatment-waning assumptions, and alternative scenarios when longer-term data become available. Validation across both arms is warranted to assess incremental outcomes and cost-effectiveness.

PMID:
42798299
Bibliographic data and abstract were imported from PubMed on 26 Sep 2026.

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