PROCC: a predictive score to identify KRAS wild type metastatic colorectal cancer patients who are likely to obtain survival benefit from panitumumab treatment.

BACKGROUND

Practice guidelines recommend panitumumab with chemotherapy to treat KRAS wild-type (WT) metastatic colorectal cancer (mCRC) patients. However, not all patients respond to this therapy. We propose a score termed "PROCC" to identify likely panitumumab responders.

METHODS

The training (TRDS) and validation (VALDS) datasets included KRAS WT mCRC patients treated with panitumumab (P) plus chemotherapy (TRDS, FOLFOX4; VALDS, FOLFIRI). TRDS included 36 diverse features used to generate synthetic representations analyzed via machine learning (ML) to identify patient subgroups, which were correlated with PFS and OS. A multivariable logistic regression model identified independent predictors to develop a predictive score.

RESULTS

ML identified two subpopulations in TRDS: SP-A (n = 162) and SP-B (n = 298). Only SP-A patients under P/FOLFOX4 showed improved OS versus FOLFOX4 (HR 0.68; p = 0.04). CEA, ALP, LDH, and platelets at baseline were used to create a predictive score ("PROCC"). For TRDS, the score had an area under the curve of 0.81. PROCC ≥8.5 correlated with lower risks of progression (HR 0.67; p = 0.03) and death (HR 0.65; p = 0.04) for P/FOLFOX4 versus FOLFOX4. Validation in VALDS confirmed similar results with FOLFIRI.

CONCLUSIONS

Based on four baseline parameters, PROCC may guide the selection of KRAS WT mCRC patients most likely to benefit from panitumumab.