Novel approach to meta-analysis of tests and clinical prediction rules with three or more risk categories

Multichotomous tests have three or more outcome or risk categories, and can provide richer information and a better fit with clinical decision-making than dichotomous tests. Our objective is to present a fully developed approach to the meta-analysis of multichotomous clinical prediction rules (CPRs) and tests, including meta-analysis of stratum specific likelihood ratios.

We have developed a novel approach to the meta-analysis of likelihood ratios for multichotomous tests that avoids the need to dichotomise outcome categories, and demonstrate its application to a sample CPR. We also review previously reported approaches to the meta-analysis of the area under the receiver operating characteristic curve (AUROCC) and meta-analysis of a measure of calibration (observed:expected) for multichotomous tests or CPRs.

Using data from 10 studies of the Cancer of the Prostate Risk Assessment (CAPRA) risk score for prostate cancer recurrence, we calculated summary estimates of the likelihood ratios for low, moderate and high risk groups of 0.40 (95% CI 0.32 to 0.49), 1.24 (95% CI 0.99 to 1.55) and 4.47 (95% CI 3.21 to 6.23), respectively. Applying the summary estimates of the likelihood ratios for each risk group to the overall prevalence of cancer recurrence in a population allows one to estimate the likelihood of recurrence for each risk group in that population.

An approach to meta-analysis of multichotomous tests or CPRs is presented. A spreadsheet for data preparation and code for R and Stata are provided for other researchers to download and use. Combined with summary estimates of the AUROCC and calibration, this is a comprehensive strategy for meta-analysis of multichotomous tests and CPRs.