Evaluation of alternate categorical tumor metrics and cut points for response categorization using the RECIST 1.1 data warehouse

Abstract

Purpose: We sought to test and validate the predictive utility of trichotomous tumor response (TriTR; complete response [CR] or partial response [PR] v stable disease [SD] v progressive disease [PD]), disease control rate (DCR; CR/PR/SD v PD), and dichotomous tumor response (DiTR; CR/PR v others) metrics using alternate cut points for PR and PD. The data warehouse assembled to guide the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 was used.

Methods: Data from 13 trials (5,480 patients with metastatic breast cancer, non-small-cell lung cancer, or colorectal cancer) were randomly split (60:40) into training and validation data sets. In all, 27 pairs of cut points for PR and PD were considered: PR (10% to 50% decrease by 5% increments) and PD (10% to 20% increase by 5% increments), for which 30% and 20% correspond to the RECIST categorization. Cox proportional hazards models with landmark analyses at 12 and 24 weeks stratified by study and number of lesions (fewer than three v three or more) and adjusted for average baseline tumor size were used to assess the impact of each metric on overall survival (OS). Model discrimination was assessed by using the concordance index (c-index).

Results: Standard RECIST cut points demonstrated predictive ability similar to the alternate PR and PD cut points. Regardless of tumor type, the TriTR, DiTR, and DCR metrics had similar predictive performance. The 24-week metrics (albeit with higher c-index point estimate) were not meaningfully better than the 12-week metrics. None of the metrics did particularly well for breast cancer.

Conclusion: Alternative cut points to RECIST standards provided no meaningful improvement in OS prediction. Metrics assessed at 12 weeks have good predictive performance.

Fig 1.

CONSORT diagram. (*) Twelve- and 24-week subsets are unique and created according to scenarios 1, 2, 3, and 6 in Appendix Figure A1. NSCLC, non–small-cell lung cancer.

Fig 2.

Forest plots of the concordance indices (c-indices) and associated 95% CIs for (A) breast cancer, (B) non–small-cell lung cancer, and (C) colorectal cancer using alternate partial response (PR) and progressive disease (PD) cut points for overall survival with the trichotomous tumor response metric on the training data sets. N(x), number of patients evaluable for the respective analysis.

Fig 3.

Forest plots of the concordance indices (c-indices) and the associated 95% CIs for (A) breast cancer, (B) non–small-cell lung cancer, and (C) colorectal cancer using alternate partial response (PR) and progressive disease (PD) cut points for overall survival with the trichotomous tumor response metric on the validation data sets. N(x), number of patients evaluable for the respective analysis.

Fig 4.

Forest plots of the concordance indices (c-indices) and the associated 95% CIs for (A) breast cancer, (B) non–small-cell lung cancer, and (C) colorectal cancer from the 12- and 24-week landmark analyses for the three categorical metrics using the training and validation data sets. DCR, disease control rate; DiTR, dichotomous tumor response; TriTR, trichotomous tumor response.

Fig 5.

Kaplan-Meier curves for subsequent overall survival for (A) breast cancer, (B) non–small-cell lung cancer, and (C) colorectal cancer using the response status at 12 (left panels) and 24 (right panels) weeks. CR, complete response; DCR, disease control rate; DiTR, dichotomous tumor response; PD, progressive disease; PR, partial response; SD, stable disease; TriTR, trichotomous tumor response.

Fig A1.

Criteria for selection of patients for the 12-week landmark analysis.

Fig A2.

Distribution of average baseline tumor size in millimeters (excluding outliers*), by tumor type. (*) Values outside Q3 + 1.5 interquartile range (IQR), and Q1 − 1.5 IQR are not shown. NSCLC, non–small-cell lung cancer.

Fig A3.

Frequency distribution of the numbers of patients with (A) breast cancer, (B) non–small-cell lung cancer, and (C) colorectal cancer, by tumor type, on the basis of the 12-week data set that fall under the categories of partial response (PR), stable disease (SD), and progressive disease (PD) based on the different alternative cut points for PR and PD.