Developing an Objective Marker to Optimize Patient Selection and Predict Survival Benefit in Early-Phase Cancer Trials

BACKGROUNDSeveral prognostic indices have been devised to optimize patient selection for phase 1 oncology trials with no consensus as to the optimal score and none qualifying as a marker of treatment response. METHODSMultivariate predictors of overall survival (OS) were tested on 118 referred patients to develop the Hammersmith Score (HS). The score's ability to predict OS, progression-free survival (PFS), and 90-day mortality (90DM) was compared with other prognostic indices. Changes in HS were recalculated during treatment. RESULTSAlbumin<35 g/L, lactate dehydrogenase>450 U/L, and sodium<135 mmol/L emerged as independent prognostic factors. These were used with equal weighting to devise the HS, a compound prognostic index ranging from 0 to 3. High (HS=2-3) score predicted worse OS (hazard ratio [HR]=6.5, P<.001), PFS (HR=2.8, P=.01), and 90DM (OR=9.0, P<.001). HS was a more accurate multivariate predictor of OS (HR=6.4, P<.001, C-index=0.72), PFS (HR=2.7, P=.03), and 90DM (area under the ROC curve 0.703) compared with other scores. Worsening of the HS during treatment predicted for shorter OS (P<.001). HS retained prognostic and predictive ability following external validation. CONCLUSIONSHS is a simple, validated index to optimize patient selection and predict survival benefit from phase 1 oncology treatments. Prospective validation is ongoing. Cancer 2014;120:262-270. (c) 2013 American Cancer Society.