Prognostic classification of patients with metastatic clear cell renal cell carcinoma (mccRCC) is instrumental for clinical trials and treatment decisions. Hence, optimal performance of prognostic models is crucial. This study aimed to develop and externally validate the new Clinical Prognostic Index in the Checkpoint Inhibitor era (CPI2) model using clinical trial data, and to externally validate the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model.
Individual patient data from the clinical trials CheckMate-214 and CheckMate-9ER were used for development and external validation of the CPI2 model, respectively. Both trials included previously untreated mccRCC patients of all IMDC prognostic groups and Karnofsky performance status of at least 70%, and randomly allocated them to receive either sunitinib or nivolumab plus ipilimumab (CheckMate-214) or nivolumab plus cabozantinib (CheckMate-9ER). Using a Cox proportional hazards model, predictors were selected from a list of patient, disease, and laboratory parameters using Akaike information criterion-based backwards selection. Bootstrapping was used to estimate coefficients and a shrinkage factor to correct for optimism. Calibration plots and Uno’s C-index for discriminative accuracy were calculated for the CPI2 model and IMDC model in both trial populations.
Data from 1096 patients included in CheckMate-214 between October, 2014, and February, 2016, and 651 patients included in CheckMate-9ER between September, 2017, and May, 2019, were used. Median follow-up was 40 months (IQR 13–94) in CheckMate-214 data and 38 months (15–53) in CheckMate-9ER data. In total, 665 (38%) of 1747 patients were aged 65 years or older; 1289 (74%) were male, and 458 (26%) were female. A prognostic model based on age, Karnofsky performance status, previous nephrectomy, metastatic locations (liver, lung, bone, and lymph node), and seven laboratory parameters (calcium, alkaline phosphatase, albumin, lactate dehydrogenase, absolute neutrophil count, lymphocyte count, and white blood cell count) was developed based on CheckMate-214 data. Classification into three prognostic groups provided discriminative accuracy at 36 months of 0·72 (95% CI 0·69–0·75) in CheckMate-214 and 0·72 (0·68–0·76) in CheckMate-9ER, which was 0·65 (0·62–0·68) and 0·61 (0·57–0·65) for the IMDC classification, respectively. Calibration showed adequate agreement between predicted and observed mortality risks. PD-L1 expression did not improve prognostic accuracy. CPI2 favourable, intermediate, and poor risk groups included 472 (43%), 366 (33%), and 258 (24%) of 1096 CheckMate-214 patients and 257 (39%), 196 (30%), and 198 (30%) of 651 CheckMate-9ER patients, respectively.
The CPI2 model, using 14 readily available clinical parameters, demonstrated improvement in discriminative accuracy compared with the IMDC model. This classification should be further validated in other trial and observational populations and be used to reanalyse heterogeneity of treatment effects of immune checkpoint inhibitor-based combination regimens in trials shaping the current and future treatment landscape.
Funding
Josephine Nefkens Foundation.
Commentary by Assoc. Prof. Carlotta Palumbo
The Clinical Prognostic Index in the Checkpoint Inhibitor era (CPI2) and risk stratification in metastatic RCC
The management of metastatic clear cell renal cell carcinoma (mccRCC) is based on patients stratification in prognostic groups. These are used to design trials, interpret subgroup analyses and guide first-line treatment. Currently, prognostic groups are based on the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model, which was built in patients treated largely with VEGFR inhibitors between 2004 and 2010. Richters and colleagues ask whether the IMDC model still adequately describes prognosis in patients receiving modern immune checkpoint inhibitor-based combinations.
The authors developed the Clinical Prognostic Index in the Checkpoint Inhibitor era (CPI2) using the CheckMate-214 cohort and then externally validated it in the CheckMate-9ER cohort. Briefly, CPI2 includes 14 variables available before treatment: age, Karnofsky performance status, previous nephrectomy, liver, lung, bone and lymph-node metastases, together with calcium, alkaline phosphatase, albumin, lactate dehydrogenase, absolute neutrophil count, lymphocyte count and white blood cell count. The authors examined non-linear associations, addressed missing data by multiple imputation, applied bootstrap shrinkage and tested the model in a separate phase 3 trial. These details matter because several weaknesses of IMDC arise from dichotomising continuous variables and assigning the same weight to each risk factor.
The improvement in discrimination was consistent. At 36 months, the C-index for the three CPI2 groups was 0.72 in both datasets; the corresponding values for IMDC were 0.65 in CheckMate-214 and 0.61 in CheckMate-9ER. Calibration in the validation cohort was acceptable, although predicted survival at 36 months was slightly lower than observed survival (50% versus 54%).
More strikingly, CPI2 changed the risk category of many patients. In CheckMate-9ER, 38% of patients considered favourable risk by IMDC moved to an intermediate or poor CPI2 group, and 41% of the IMDC-intermediate group moved to CPI2 favourable risk. This is enough discordance to question whether IMDC-stratified results from pivotal trials tell the whole story, especially for favourable-risk disease.
The study also has relevant limitations. Both datasets were derived from trials sponsored by the same company, and the experimental arms shared a nivolumab backbone. Patients with brain metastases, non-clear cell histology or a Karnofsky performance status below 70% were excluded, leaving uncertainty about the model’s performance in routine clinical practice. In addition, lymphocyte count was missing in 29% of CheckMate-9ER patients.
The next step should be validation in independent trials and unselected real-world cohorts, followed by reanalysis of treatment effects across CPI2 risk groups. Until these data are available, CPI2 should complement rather than replace IMDC. Nevertheless, the study raises legitimate concerns about relying on IMDC alone and provides a sound basis for improving prognostic stratification in the ICI era.