A clinical scoring tool validated with machine learning for predicting severe hand-foot syndrome from sorafenib in hepatocellular carcinoma.

PURPOSE: Sorafenib is an effective therapy for advanced hepatocellular carcinoma (HCC). Hand-foot syndrome (HFS) is a serious adverse effect associated with sorafenib therapy. This study aimed to develop an updated clinical prediction tool that allows personalized prediction of HFS following sorafenib initiation. METHODS: Individual participant data from Phase III clinical trial NCT00699374 were used in Cox proportional hazard analysis of the association between pre-treatment clinicopathological data and grade ≥ 3 HFS occurring within the first 365 days of sorafenib treatment for advanced HCC. Multivariable prediction models were developed using stepwise forward inclusion and backward deletion and internally validated using a random forest machine learning approach. RESULTS: Of 542 patients, 116 (21%) experienced grades ≥ 3 HFS. The prediction tool was optimally defined by sex (male vs female), haemoglobin (< 130 vs ≥ 130 g/L) and bilirubin (< 10 vs 10-20 vs ≥ 20 µmol/L). The prediction tool was able to discriminate subgroups with significantly different risks of grade ≥ 3 HFS (P ≤ 0.001). The high (score = 3 +)-, intermediate (score = 2)- and low (score = 0-1)-risk subgroups had 40%, 27% and 14% probability of developing grade ≥ 3 HFS within the first 365 days of sorafenib treatment, respectively. CONCLUSION: A clinical prediction tool defined by female sex, high haemoglobin and low bilirubin had high discrimination for predicting HFS risk. The tool may enable improved evaluation of personalized risks of HFS for patients with advanced HCC initiating sorafenib.

Prediction of severe neutropenia and diarrhoea in breast cancer patients treated with abemaciclib.

INTRODUCTION: Neutropenia and diarrhoea are common and potentially serious adverse events associated with abemaciclib in advanced breast cancer (ABC), and the risk factors have been minimally explored. The study aimed to develop clinical prediction tools that allow personalized predictions of neutropenia and diarrhoea following abemaciclib initiation. MATERIALS AND METHODS: Data was pooled from MONARCH 1, 2 and 3 trials investigating abemaciclib. Cox proportional hazard analysis was used to assess the association between pre-treatment clinicopathological data and grade ≥3 diarrhoea and neutropenia occurring within the first 365 days of abemaciclib use. RESULTS: Older age was associated with increased risk of grade ≥3 diarrhoea [HR [95%CI] for age > 70: 1.72 [1.14-2.58]; P = 0.009]. A clinical prediction tool for abemaciclib induced grade ≥3 neutropenia was optimally defined by race, ECOGPS and white blood cell count. Large discrimination between subgroups was observed; the highest risk subgroup had a 64% probability of grade ≥3 neutropenia within the first 365 days of abemaciclib (150 mg twice daily) + fulvestrant/NSAI, compared to 5% for the lowest risk subgroup. CONCLUSION: The study identified advanced age as significantly associated with an increased risk of abemaciclib induced grade ≥ 3 diarrhoea. A clinical prediction tool, defined by race, ECOGPS and pre-treatment white blood cell count, was able to discriminate subgroups with significantly different risks of grade ≥3 neutropenia following abemaciclib initiation. The tool may enable improved interpretation of personalized risks and the risk-benefit ratio of abemaciclib.