Abstract
Purpose: The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. Patients and Methods: Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and 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 cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. Conclusion: 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.
| Original language | English |
|---|---|
| Pages (from-to) | 996-1004 |
| Number of pages | 9 |
| Journal | Journal of Clinical Oncology |
| Volume | 30 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Mar 20 2012 |
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ASJC Scopus subject areas
- Cancer Research
- Oncology
- Medicine(all)
Cite this
Patient selection for oncology phase I trials : A multi-institutional study of prognostic factors. / Olmos, David; A'Hern, Roger P.; Marsoni, Silvia; Morales, Rafael; Gomez-Roca, Carlos; Verweij, Jaap; Voest, Emile E.; Schof̈fski, Patrick; Ang, Joo Ern; Penel, Nicolas; Schellens, Jan H.; Del Conte, Gianluca; Brunetto, Andre T.; Evans, T. R Jeffry; Wilson, Richard; Gallerani, Elisa; Plummer, Ruth; Tabernero, Josep; Soria, Jean Charles; Kaye, Stan B.
In: Journal of Clinical Oncology, Vol. 30, No. 9, 20.03.2012, p. 996-1004.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Patient selection for oncology phase I trials
T2 - A multi-institutional study of prognostic factors
AU - Olmos, David
AU - A'Hern, Roger P.
AU - Marsoni, Silvia
AU - Morales, Rafael
AU - Gomez-Roca, Carlos
AU - Verweij, Jaap
AU - Voest, Emile E.
AU - Schof̈fski, Patrick
AU - Ang, Joo Ern
AU - Penel, Nicolas
AU - Schellens, Jan H.
AU - Del Conte, Gianluca
AU - Brunetto, Andre T.
AU - Evans, T. R Jeffry
AU - Wilson, Richard
AU - Gallerani, Elisa
AU - Plummer, Ruth
AU - Tabernero, Josep
AU - Soria, Jean Charles
AU - Kaye, Stan B.
PY - 2012/3/20
Y1 - 2012/3/20
N2 - Purpose: The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. Patients and Methods: Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and 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 cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. Conclusion: 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.
AB - Purpose: The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. Patients and Methods: Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and 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 cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. Conclusion: 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84857055503&partnerID=8YFLogxK
U2 - 10.1200/JCO.2010.34.5074
DO - 10.1200/JCO.2010.34.5074
M3 - Article
C2 - 22355064
AN - SCOPUS:84857055503
VL - 30
SP - 996
EP - 1004
JO - Journal of Clinical Oncology
JF - Journal of Clinical Oncology
SN - 0732-183X
IS - 9
ER -