Patient Selection for Oncology Phase I Trials: a multi-institutional study of prognostic factors

ESMO Young Oncologists Journal Club

Jesus Corral


The appropriate selection of patients for early clinical trials presents a major challenge. Previous institutional studies focusing on this problem were limited by small size and by interpractice heterogeneity, including the validated Royal Marsden Hospital (RMH) score, which comprises three variables: serum albumin, number of metastatic sites, and lactate dehydrogenase (LDH). This study aims to analyse antitumour activity and identify objective clinicopathological prognostic factors to guide risk-benefit assessments by using a large database from multiple phase I trials.

Summary and discussion of the presented study

This is a retrospective multicenter study comprising all patients treated in phase I trials from January 2005 to December 2007 within the European Drug Development Network (EDDN), an international consortium involving 14 Oncology Drug Development Units. The primary objective was to generate and validate a prognostic model for 90-day mortality. Secondary objectives included an estimation of early 21-day trial discontinuation, a description of risk factors associated to, and an analysis of overall response rate (ORR), progression free survival (PFS), and overall survival (OS) in this context.

Data were collected from 2,182 eligible patients. Sixty-three percent of patients were treated in trials involving single agents (88% of which were first-in-human) and the remainder in trials involving combinations of novel or established therapies.

According to the primary objective of the study, authors used two models to derive and validate prognostic models of 90-day survival by using multivariate logistic regression analysis. The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, LDH, alkaline phosphatase (ALP), number of metastatic sites, clinical tumour growth rate, lymphocytes, and white blood cells (WBC). Two different models of prognostic scores for 90-day mortality were generated by using these factors, including or excluding PS; both achieved specificities of more than 85% and sensitivities of approximately 50% when using a score cut-off of 5 or higher. These models did not resulted superior to the previously published RMH score in their ability to predict 90-day mortality.

Regarding the secondary objectives, a few endpoints were analysed. Firstly, trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. The prognostic factors related to 21-day discontinuation rate by relative risk included PS 1-2 versus 0, increased LDH, increased ALP, more than two metastatic sites, and treatment based on conventional chemotherapy or not. ORR was 10%, and disease stabilization rates at 3 and 6 months were 26% and 10%, respectively. It resulted different significantly between patients treated in trials containing or not conventional cytotoxics (31% versus 61%, p<0.001). The median PFS was 10.9 weeks, with a median OS of 38.6 weeks.

Current study represents the first European multi-institutional approach to know, based on individual patients data, the efficacy and survival rates obtained into phase I drug development units in the modern era of targeted agents. Previous studies were based on summaries of phase I clinical trials using mainly cytotoxic chemotherapy. To pursue the main objective of the trial, eight prognostic variables were identified: LDH, serum albumin, and number of metastatic sites (previously described as part of the RMH score), WBC, lymphocytes, PS, ALP, and the time per treatment index (TPTi), a log ratio of the time interval between diagnosis of advanced/metastatic cancer and phase I trial entry over the number of lines of systemic treatment. Curiously, neither the time from diagnosis to phase I trial entry nor the number of systemic treatment lines were considered independent prognostic factors, which had been identified in previous phase I trials: however, authors found the prognostic value of TPTi, which comprises both variables. It could be explained by tumour and treatment heterogeneity, or because TPTi explained more accurately the biologic behaviour before study entry.

In terms of efficacy, this study showed OS and objective response rates consistent with those in other recent studies. A strong negative prognostic value of PS 2 was detected, supporting results from older series. In addition to providing an update on safety, they obtained a low rate of deaths related with toxicity (0.4%) and identified the main cause for early trial discontinuation was related to disease progression.

To understand the impact of using these models in patient selection for phase I trials in everyday practice, authors illustrated the prognostic model in 200 phase I eligible patients. Overall 90-day mortality rate was 16.5%, that is to say that more than 70% of patients who died within 90 days would have discontinued the trial within 21 days. Selection of patients with better prognosis will improve overall phase I trial results, but it will also reduce overall recruitment by 20%.


Patient selection using any of these prognostic scores will reduce non-drug-related 90-day mortality among patients enrolled in phase I trials by 50%. However, this can be achieved only by an overall reduction in recruitment to phase I studies of 20%, more than half of whom would in fact have survived beyond 90 days. Predictive molecular biomarkers next to routine clinical and analytic parameters will improve patient selection in this context. Further collaborations between phase I units, such as the EDDN, will be an important step forward to optimize the conduct of phase I trials.

Patient Selection for Oncology Phase I Trials: a multi-institutional study of prognostic factors
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