Performance Status Restriction in Phase III Cancer Clinical Trials

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  • 1 The University of Texas MD Anderson Cancer Center, Houston, Texas;
  • 2 Baylor College of Medicine, Houston, Texas;
  • 3 The Johns Hopkins University School of Medicine, Baltimore, Maryland;
  • 4 The University of Texas Health Science Center McGovern Medical School, Houston, Texas;
  • 5 The University of Tennessee Health Science Center College of Medicine, Memphis, Tennessee;
  • 6 West Cancer Center and Research Institute, Memphis, Tennessee;
  • 7 University of Frankfurt, Frankfurt, Germany;
  • 8 German Cancer Research Center, Heidelberg, Germany;
  • 9 German Cancer Consortium, Frankfurt, Germany;
  • 10 Frankfurt Cancer Institute, Frankfurt, Germany;
  • 11 University of Michigan, Ann Arbor, Michigan; and
  • 12 Oregon Health and Science University, Portland, Oregon.
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Background: Patients with good performance status (PS) tend to be favored in randomized clinical trials (RCTs), possibly limiting the generalizability of trial findings. We aimed to characterize trial-related factors associated with the use of PS eligibility criteria and analyze patient accrual breakdown by PS. Methods: Adult, therapeutic, multiarm phase III cancer-specific RCTs were identified through ClinicalTrials.gov. PS data were extracted from articles. Trials with a PS restriction ECOG score ≤1 were identified. Factors associated with PS restriction were determined, and the use of PS restrictions was analyzed over time. Results: In total, 600 trials were included and 238,213 patients had PS data. Of those trials, 527 studies (87.8%) specified a PS restriction cutoff, with 237 (39.5%) having a strict inclusion criterion (ECOG PS ≤1). Enrollment criteria restrictions based on PS (ECOG PS ≤1) were more common among industry-supported trials (P<.001) and lung cancer trials (P<.001). Nearly half of trials that led to FDA approval included strict PS restrictions. Most patients enrolled across all trials had an ECOG PS of 0 to 1 (96.3%). Even among trials that allowed patients with ECOG PS ≥2, only 8.1% of those enrolled had a poor PS. Trials of lung, breast, gastrointestinal, and genitourinary cancers all included <5% of patients with poor PS. Finally, only 4.7% of patients enrolled in trials that led to subsequent FDA approval had poor PS. Conclusions: Use of PS restrictions in oncologic RCTs is pervasive, and exceedingly few patients with poor PS are enrolled. The selective accrual of healthier patients has the potential to severely limit and bias trial results. Future trials should consider a wider cancer population with close toxicity monitoring to ensure the generalizability of results while maintaining patient safety.

Submitted March 7, 2020; accepted for publication April 16, 2020.

Author contributions: Study concept and design: Jaoude, Kouzy, Taniguchi, Ludmir. Data collection: Jaoude, Kouzy, Mainwaring, Lin, Miller, Jethanandani, Espinoza, Ludmir. Data analysis and interpretation: All authors. Manuscript preparation: All authors.

Disclosures: Dr. VanderWalde has disclosed that he receives consulting fees from Vector Oncology. Dr. B.D. Smith has disclosed that he has received grant/research support from Varian Medical Systems, and has an equity interest in Oncora Medical. Dr. Fuller has disclosed that he receives royalty income from Demos Medical Publishing, and honoraria from Elekta AB. Dr. Das has disclosed that he receives consulting fees from Adlai Nortye. Dr. Jagsi has disclosed that she has is a scientific advisor for Equity Quotient, has received honoraria from Amgen and Vizient, and has received grant/research support from the Doris Duke Foundation, the Greenwall Foundation, the Komen Foundation, and Blue Cross Blue Shield of Michigan. The remaining authors have disclosed that they have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Funding: Dr. Taniguchi is supported by funding from NIH (award R01CA227517-01A1), Cancer Prevention & Research Institute of Texas (CPRIT; grant RR140012), V Foundation (V2015-22), the Kimmel Foundation, Sabin Family Foundation Fellowship, and the McNair Foundation. This manuscript is also supported by NIH P30 CA016672.

Correspondence: Cullen M. Taniguchi, MD, PhD, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 1050, Houston, TX 77030. Email: ctaniguchi@mdanderson.org; and Ethan B. Ludmir, MD, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Unit 1422, Houston, TX 77030. Email: ebludmir@mdanderson.org

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  • 1.

    Gronlund B, Høgdall C, Hansen HH, . Performance status rather than age is the key prognostic factor in second-line treatment of elderly patients with epithelial ovarian carcinoma. Cancer 2002;94:19611967.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Jang RW, Caraiscos VB, Swami N, . Simple prognostic model for patients with advanced cancer based on performance status. J Oncol Pract 2014;10:e335341.

  • 3.

    Kocher HM, Patel S, Linklater K, . Increase in the incidence of oesophagogastric carcinoma in the South Thames region: an epidemiological study. Br J Surg 2000;87:362373.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Prigerson HG, Bao Y, Shah MA, . Chemotherapy use, performance status, and quality of life at the end of life. JAMA Oncol 2015;1:778784.

  • 5.

    Oken MM, Creech RH, Tormey DC, . Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol 1982;5:649655.

  • 6.

    Karnofsky DA, Burchenal JH. The clinical evaluation of chemotherapeutic agents in cancer. In: MacLeod CM, ed. Evaluation of Chemotherapeutic Agents. New York, NY: Columbia University Press; 1949:191–205.

  • 7.

    West H, Jin J. Performance status in patients with cancer. JAMA Oncol 2015;1:998.

  • 8.

    Leal AD, Allmer C, Maurer MJ, . Variability of performance status assessment between patients with hematologic malignancies and their physicians. Leuk Lymphoma 2018;59:695701.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Sørensen JB, Klee M, Palshof T, . Performance status assessment in cancer patients. An inter-observer variability study. Br J Cancer 1993;67:773775.

  • 10.

    Capewell S, Sudlow MF. Performance and prognosis in patients with lung cancer. Thorax 1990;45:951956.

  • 11.

    Salloum RG, Smith TJ, Jensen GA, . Survival among non-small cell lung cancer patients with poor performance status after first line chemotherapy. Lung Cancer 2012;77:545549.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Jin S, Pazdur R, Sridhara R. Re-evaluating eligibility criteria for oncology clinical trials: analysis of investigational new drug applications in 2015. J Clin Oncol 2017;35:37453752.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Lilenbaum RC, Cashy J, Hensing TA, . Prevalence of poor performance status in lung cancer patients: implications for research. J Thorac Oncol 2008;3:125129.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Buccheri G, Ferrigno D, Tamburini M. Karnofsky and ECOG performance status scoring in lung cancer: a prospective, longitudinal study of 536 patients from a single institution. Eur J Cancer 1996;32:11351141.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Corrêa GTB, Bandeira GA, Cavalcanti BG, . Analysis of ECOG performance status in head and neck squamous cell carcinoma patients: association with sociodemographical and clinical factors, and overall survival. Support Care Cancer 2012;20:26792685.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Ludmir EB, Mainwaring W, Lin TA, . Factors associated with age disparities among cancer clinical trial participants. JAMA Oncol 2019;5:17691773.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Liberati A, Altman DG, Tetzlaff J, . The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 2009;339:b2700.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Murthy VH, Krumholz HM, Gross CP. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA 2004;291:27202726.

  • 19.

    George SL. Reducing patient eligibility criteria in cancer clinical trials. J Clin Oncol 1996;14:13641370.

  • 20.

    Shah NJ, Blackburn M, Cook MR, . Real-world outcomes of underrepresented patient populations treated with immune checkpoint inhibitors (ICIs): African American descent, poor ECOG performance status, and chronic viral infections [abstract]. J Clin Oncol 2019;37(Suppl):Abstract 2587.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Hoang T, Xu R, Schiller JH, . Clinical model to predict survival in chemonaive patients with advanced non-small-cell lung cancer treated with third-generation chemotherapy regimens based on Eastern Cooperative Oncology Group data. J Clin Oncol 2005;23:175183.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Perry JR, Laperriere N, O’Callaghan CJ, . Short-course radiation plus temozolomide in elderly patients with glioblastoma. N Engl J Med 2017;376:10271037.

  • 23.

    Chino F, Zafar SY. Financial toxicity and equitable access to clinical trials. Am Soc Clin Oncol Educ Book 2019;39:1118.

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