An original approach was used to better evaluate the capacity of a prognostic marker using published survival curves

Predicting chronic disease evolution from a prognostic marker is a key field of research in clinical epidemiology. However, the prognostic capacity of a marker is not systematically evaluated using the appropriate methodology. We proposed the use of simple equations to calculate time-dependent sensitivity and specificity based on published survival curves and other time-dependent indicators as predictive values, likelihood ratios, and posttest probability ratios to reappraise prognostic marker accuracy.

The methodology is illustrated by back calculating time-dependent indicators from published articles presenting a marker as highly correlated with the time to event, concluding on the high prognostic capacity of the marker, and presenting the Kaplan-Meier survival curves. The tools necessary to run these direct and simple computations are available online at http://www.divat.fr/en/online-calculators/evalbiom.

Our examples illustrate that published conclusions about prognostic marker accuracy may be overoptimistic, thus giving potential for major mistakes in therapeutic decisions.

Our approach should help readers better evaluate clinical articles reporting on prognostic markers. Time-dependent sensitivity and specificity inform on the inherent prognostic capacity of a marker for a defined prognostic time. Time-dependent predictive values, likelihood ratios, and posttest probability ratios may additionally contribute to interpret the marker's prognostic capacity.