Patient selection for oncology phase I trials: A multi-institutional study of prognostic factors

David Olmos, Roger P. A'Hern, Silvia Marsoni, Rafael Morales, Carlos Gomez-Roca, Jaap Verweij, Emile E. Voest, Patrick Schof̈fski, Joo Ern Ang, Nicolas Penel, Jan H. Schellens, Gianluca Del Conte, Andre T. Brunetto, T. R Jeffry Evans, Richard Wilson, Elisa Gallerani, Ruth Plummer, Josep Tabernero, Jean Charles Soria, Stan B. Kaye

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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 languageEnglish
Pages (from-to)996-1004
Number of pages9
JournalJournal of Clinical Oncology
Volume30
Issue number9
DOIs
Publication statusPublished - Mar 20 2012

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Patient Selection
Mortality
L-Lactate Dehydrogenase
Alkaline Phosphatase
Disease Progression
Albumins
Logistic Models
Regression Analysis
Clinical Trials
Databases
Lymphocytes
Growth
Pharmaceutical Preparations
Neoplasms

ASJC Scopus subject areas

  • Cancer Research
  • Oncology
  • Medicine(all)

Cite this

Olmos, D., A'Hern, R. P., Marsoni, S., Morales, R., Gomez-Roca, C., Verweij, J., ... Kaye, S. B. (2012). Patient selection for oncology phase I trials: A multi-institutional study of prognostic factors. Journal of Clinical Oncology, 30(9), 996-1004. https://doi.org/10.1200/JCO.2010.34.5074

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 journalArticle

Olmos, D, A'Hern, RP, Marsoni, S, Morales, R, Gomez-Roca, C, Verweij, J, Voest, EE, Schof̈fski, P, Ang, JE, Penel, N, Schellens, JH, Del Conte, G, Brunetto, AT, Evans, TRJ, Wilson, R, Gallerani, E, Plummer, R, Tabernero, J, Soria, JC & Kaye, SB 2012, 'Patient selection for oncology phase I trials: A multi-institutional study of prognostic factors', Journal of Clinical Oncology, vol. 30, no. 9, pp. 996-1004. https://doi.org/10.1200/JCO.2010.34.5074
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. / Patient selection for oncology phase I trials : A multi-institutional study of prognostic factors. In: Journal of Clinical Oncology. 2012 ; Vol. 30, No. 9. pp. 996-1004.
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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.",
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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.

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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.

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