Improving the pre-screening of eligible patients in order to increase enrollment in cancer clinical trials

Boris Campillo-Gimenez, Camille Buscail, Oussama Zekri, Brigitte Laguerre, Elisabeth Le Prisé, Renaud De Crevoisier, Marc Cuggia, Boris Campillo-Gimenez, Camille Buscail, Oussama Zekri, Brigitte Laguerre, Elisabeth Le Prisé, Renaud De Crevoisier, Marc Cuggia

Abstract

Background: The performance of randomized controlled trials (RCTs) is often hindered by recruitment difficulties. This study aims to explore the pre-screening phase of four prostate cancer RCTs to identify the impact of a systematic pre-selection of eligible patients for RCT recruitment.

Methods: The pre-screening of four RCTs opened at the Comprehensive Cancer Center in Rennes was analyzed retrospectively (French Genitourinary Tumor Group (GETUG) 14, 15, 16, and 17). Data were extracted from electronic multidisciplinary cancer (MDC) reports and manually completed by physicians and medical secretaries. These data were the main source of information for clinicians to discuss treatment alternatives during MDC sessions. The pre-screening decisions made by the clinicians during these MDC meetings were compared with those made after a systematic review of the MDC reports by a clinical research assistant (CRA). Any inconsistencies in decisions between the CRA and the MDC physicians were corrected by the principal investigator (PI).

Results: The pre-screening rate was 9.1% during the MDC meetings, while it was estimated to be 12.9% after the final review by the PI, and 29% after the systematic review by the CRA. The study showed that 77% and 67% of the MDC reports did not mention clinical and pathological Tumor, lymph node and metastasis classification of malignant tumors (TNM) staging, respectively, and that 35 of the CRA's 47 proposals rejected by the PI concerned implicit information (not specified in the MDC reports). Only one patient was proposed by the PI, and none by the CRA.

Conclusions: These results confirm that pre-screening could be improved by a systematic review of the medical reports. They also highlight the fact that missing data in electronic MDC reports leads to over-enrollment of non-eligible patients, but not to over-exclusion of eligible patients. Thus, our study confirms the potential gain in using semi-automated pre-selection of MDC reports, in order to avoid missing out on patients eligible for RCTs.

Trial registration: The trials evaluated in this study were previously registered with clinicaltrials.gov (registration number: NCT00104741 on 3 March 2005; NCT00104715 on 3 March 2005; NCT00423475 on 16 January 2007; and NCT00667069 on 24 April 2008).

Figures

Figure 1
Figure 1
The therapeutic decision-making process for patients with cancer in Brittany (France), including the multidisciplinary cancer (MDC) meeting. Step one: MDC meeting request by a treating physician concerning a patient; step two: MDC meeting scheduled by the MDC secretary; step three: presentation of the MDC report during the MDC meeting; step four: registration of the therapeutic decision in the oncologic electronic health records (EHR) and feedback to the treating physician.
Figure 2
Figure 2
Evaluation design of the multidisciplinary cancer (MDC) team’s pre-screening decisions. Step one: extraction of the MDC reports from the oncologic electronic health records (her); step two: Extraction of the MDC team’s pre-screening decisions from the oncologic EHR; Step 3: systematic review of the MDC reports by the clinical research assistant (CRA); step four: comparison of the pre-screening decisions made by the CRA and the MDC team; step five: principal investigator’s review of the MDC reports corresponding to the discrepancies between the CRA’s decisions and the MDC team’s decisions; step six: final pre-screening decisions (gold standard) including the principal investigator’s decisions.
Figure 3
Figure 3
Venn diagram of the pre-screening of patients eligible for four randomized clinical trials carried out at the Comprehensive Cancer Center in Rennes (GETUG 14, 15, 16, and 17). Pre-screening was based on the physicians’ decisions during the multidisciplinary cancer meetings (MDC team’s decisions), the decisions of the clinical research assistant (CRA’s decisions), and the principal investigator (PI’s decisions) after a systematic review of the MDC reports.

References

    1. Caldwell PHY, Hamilton S, Tan A, Craig JC. Strategies for increasing recruitment to randomised controlled trials: systematic review. PLoS Med. 2010;7:e1000368. doi: 10.1371/journal.pmed.1000368.
    1. Bleyer A, Montello M, Budd T, Saxman S. National survival trends of young adults with sarcoma: lack of progress is associated with lack of clinical trial participation. Cancer. 2005;103:1891–1897. doi: 10.1002/cncr.20995.
    1. Chow CJ, Habermann EB, Abraham A, Zhu Y, Vickers SM, Rothenberger DA, Al-Refaie WB. Does enrollment in cancer trials improve survival? J Am Coll Surg. 2013;216:774–780. doi: 10.1016/j.jamcollsurg.2012.12.036.
    1. Murthy VH. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA. 2004;291:2720–2726. doi: 10.1001/jama.291.22.2720.
    1. Lassale C, Sibenaler C, Behier J-M, Pletan Y, Courcier S. France, an attractive country for international clinical research: 2010 survey assessed by Leem (French association of pharmaceutical companies) Therapie. 2011;66:1–15. doi: 10.2515/therapie/2011007.
    1. Grand MM, O’Brien PC. Obstacles to participation in randomised cancer clinical trials: a systematic review of the literature. J Med Imaging Radiat Oncol. 2012;56:31–39. doi: 10.1111/j.1754-9485.2011.02337.x.
    1. Mills EJ, Seely D, Rachlis B, Griffith L, Wu P, Wilson K, Ellis P, Wright JR. Barriers to participation in clinical trials of cancer: a meta-analysis and systematic review of patient-reported factors. Lancet Oncol. 2006;7:141–148. doi: 10.1016/S1470-2045(06)70576-9.
    1. Neuzillet Y, Négrier S, Fizazi K, Pignot G, Benchikh El Fegoun A, Guillotreau J, Culine S. The French clinical trials ongoing (GETUG and AFU) on urothelial carcinomas, kidney and prostate cancers. Prog En Urol J Assoc Fr Urol Société Fr Urol. 2010;20(Suppl 1):S84–S89. doi: 10.1016/S1166-7087(10)70035-X.
    1. R Core Team . R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2014.
    1. Besana P, Cuggia M, Zekri O, Bourde A, Burgun A. Using Semantic Web Technologies for Clinical Trial Recruitment. In: PatelSchneider PF, Pan Y, Hitzler P, Mika P, Zhang L, Pan JZ, Horrocks I, Glimm B, editors. Semantic Web-Iswc 2010, Pt Ii. Berlin: Springer-Verlag Berlin; 2010. pp. 34–49.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe