ArticleBMC medical research methodology2026
The choice of time scales in survival analysis has implications: calendar time versus patients' time-to-event.
Article in BMC medical research methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the EvaCoM project, a retrospective cohort study of Germany-wide health insurance data of 29607 geriatric patients with fractures, the use of different time scales led to contradicting estimates in the Cox proportional hazards model. Here, the impact of quality audit, resulting in certification, of healthcare providers was of interest, with possible time scales being calendar time in which the audit acts or a patient's time-to-event. For the analysis the patients were divided into groups depending on whether the certification occurred before or after the patient's hospitalization, which adds a temporal component to the intervention (treatment in a certified hospital or not). A Cox model in calendar time found a harmful association of the audit with mortality (hazard ratio (HR) 1.13; 95% CI [1.04-1.23]), but in "time since hospital admission" no significant association was found (HR 1.04 [0.99-1.10]).
methodsTo investigate these contradictions, the hazards in "time since hospital admission" are parametrically approximated with piecewise linear functions and transformed to calendar time by deriving patient-specific hazards based on their hospital admission date. A Poisson regression with both time scales simultaneously is used to investigate the contradictory results further. Matching is used to analyse the association in calendar time without using an additional time scale.
resultsThe analysis of the approximated and transformed hazards leads to the conclusion that using calendar time causes a structural bias, because, in calendar time, patients of the pre-certification group enter the study earlier than those in the post-certification group. In combination with time-dependent and decreasing hazards, this leads to an artificial increase of the hazard ratio. A Poisson regression using both time scales (HR 1.00 [0.92-1.08]) and a Cox regression on matched data (HR 0.99 [0.90-1.09]) confirmed this result, finding no significant association between audits and mortality.
conclusionsIn EvaCoM, the estimation of significant association in calendar time is a consequence of a structural bias caused by patients being shifted in calendar time and not a true harmful effect. The choice of time scale may severely impact the results. We present methods to disentangle the effects of different time scales.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.