title: Predicting Low Accrual in the National Cancer Institute's Cooperative Group Clinical Trials.
abstract: BACKGROUND
  The extent to which trial-level factors differentially influence accrual to trials has not been comprehensively studied. Our objective was to evaluate the empirical relationship and predictive properties of putative risk factors for low accrual in the National Cancer Institute's (NCI's) Cooperative Group Program, now the National Clinical Trials Network (NCTN).
  
  
  METHODS
  Data from 787 phase II/III adult NCTN-sponsored trials launched between 2000 and 2011 were used to develop a logistic regression model to predict low accrual, defined as trials that closed with or were accruing at less than 50% of target; 46 trials opened between 2012 and 2013 were used for prospective validation. Candidate predictors were identified from a literature review and expert interviews; final predictors were selected using stepwise regression. Model performance was evaluated by calibration and discrimination via the area under the curve (AUC). All statistical tests were two-sided.
  
  
  RESULTS
  Eighteen percent (n = 145) of NCTN-sponsored trials closed with low accrual or were accruing at less than 50% of target three years or more after initiation. A multivariable model of twelve trial-level risk factors had good calibration and discrimination for predicting trials with low accrual (AUC in trials launched 2000-2011 = 0.739, 95% confidence interval [CI] = 0.696 to 0.783]; 2012-2013: AUC = 0.732, 95% CI = 0.547 to 0.917). Results were robust to different definitions of low accrual and predictor selection strategies.
  
  
  CONCLUSIONS
  We identified multiple characteristics of NCTN-sponsored trials associated with low accrual, several of which have not been previously empirically described, and developed a prediction model that can provide a useful estimate of accrual risk based on these factors. Future work should assess the role of such prediction tools in trial design and prioritization decisions.
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA (CSB, SDR, CLM, JJC, AB, DLV) and the Hutchinson Institute for Outcomes Research, Fred Hutchinson Cancer Research Center (SDR).
authors.forename: Caroline S
authors.initials: CS
authors.lastname: Bennette
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA (CSB, SDR, CLM, JJC, AB, DLV) and the Hutchinson Institute for Outcomes Research, Fred Hutchinson Cancer Research Center (SDR).
authors.forename: Scott D
authors.initials: SD
authors.lastname: Ramsey
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA (CSB, SDR, CLM, JJC, AB, DLV) and the Hutchinson Institute for Outcomes Research, Fred Hutchinson Cancer Research Center (SDR).
authors.forename: Cara L
authors.initials: CL
authors.lastname: McDermott
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA (CSB, SDR, CLM, JJC, AB, DLV) and the Hutchinson Institute for Outcomes Research, Fred Hutchinson Cancer Research Center (SDR).
authors.forename: Josh J
authors.initials: JJ
authors.lastname: Carlson
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA (CSB, SDR, CLM, JJC, AB, DLV) and the Hutchinson Institute for Outcomes Research, Fred Hutchinson Cancer Research Center (SDR).
authors.forename: Anirban
authors.initials: A
authors.lastname: Basu
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA (CSB, SDR, CLM, JJC, AB, DLV) and the Hutchinson Institute for Outcomes Research, Fred Hutchinson Cancer Research Center (SDR).
authors.forename: David L
authors.initials: DL
authors.lastname: Veenstra
mesh_terms: D017322:Clinical Trials, Phase II as Topic / Q000191:economics; D017326:Clinical Trials, Phase III as Topic / Q000191:economics; D006801:Humans; D016015:Logistic Models; D015337:Multicenter Studies as Topic / Q000191:economics; D054547:National Cancer Institute (U.S.); D018579:Patient Selection; D015203:Reproducibility of Results; D012107:Research Design; D012109:Research Support as Topic; D012307:Risk Factors; D014481:United States