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Wong LY, Li Y, Elliott IA, Backhus LM, Berry MF, Shrager JB, Oh DS. Randomized controlled trials in lung cancer surgery: How are we doing? JTCVS OPEN 2024; 18:234-252. [PMID: 38690441 PMCID: PMC11056451 DOI: 10.1016/j.xjon.2024.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 01/09/2024] [Accepted: 01/11/2024] [Indexed: 05/02/2024]
Abstract
Objective Randomized control trials are considered the highest level of evidence, yet the scalability and practicality of implementing randomized control trials in the thoracic surgical oncology space are not well described. The aim of this study is to understand what types of randomized control trials have been conducted in thoracic surgical oncology and ascertain their success rate in completing them as originally planned. Methods The ClinicalTrials.gov database was queried in April 2023 to identify registered randomized control trials performed in patients with lung cancer who underwent surgery (by any technique) as part of their treatment. Results There were 68 eligible randomized control trials; 33 (48.5%) were intended to examine different perioperative patient management strategies (eg, analgesia, ventilation, drainage) or to examine different intraoperative technical aspects (eg, stapling, number of ports, port placement, ligation). The number of randomized control trials was relatively stable over time until a large increase in randomized control trials starting in 2016. Forty-four of the randomized control trials (64.7%) were open-label studies, 43 (63.2%) were conducted in a single facility, 66 (97.1%) had 2 arms, and the mean number of patients enrolled per randomized control trial was 236 (SD, 187). Of 21 completed randomized control trials (31%), the average time to complete accrual was 1605 days (4.4 years) and average time to complete primary/secondary outcomes and adverse events collection was 2125 days (5.82 years). Conclusions Given the immense investment of resources that randomized control trials require, these findings suggest the need to scrutinize future randomized control trial proposals to assess the likelihood of successful completion. Future study is needed to understand the various contributing factors to randomized control trial success or failure.
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Affiliation(s)
- Lye-Yeng Wong
- Department of Cardiothoracic Surgery, Stanford University Medical Center, Stanford, Calif
| | - Yanli Li
- Department of Medical Affairs, Intuitive Surgical, Sunnyvale, Calif
| | - Irmina A. Elliott
- Department of Cardiothoracic Surgery, Stanford University Medical Center, Stanford, Calif
- VA Palo Alto Health Care System, Palo Alto, Calif
| | - Leah M. Backhus
- Department of Cardiothoracic Surgery, Stanford University Medical Center, Stanford, Calif
- VA Palo Alto Health Care System, Palo Alto, Calif
| | - Mark F. Berry
- Department of Cardiothoracic Surgery, Stanford University Medical Center, Stanford, Calif
- VA Palo Alto Health Care System, Palo Alto, Calif
| | - Joseph B. Shrager
- Department of Cardiothoracic Surgery, Stanford University Medical Center, Stanford, Calif
- VA Palo Alto Health Care System, Palo Alto, Calif
| | - Daniel S. Oh
- Department of Medical Affairs, Intuitive Surgical, Sunnyvale, Calif
- Department of Cardiothoracic Surgery, VA Palo Alto Health Care System, Palo Alto, Calif
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Zhang S, Zhang J, Liu S, Pang H, Stinchcombe TE, Wang X. Enrollment Success, Factors, and Prediction Models in Cancer Trials (2008-2019). JCO Oncol Pract 2023; 19:1058-1068. [PMID: 37793091 PMCID: PMC10667018 DOI: 10.1200/op.23.00147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/15/2023] [Accepted: 08/15/2023] [Indexed: 10/06/2023] Open
Abstract
PURPOSE To investigate the enrollment success rate of cancer clinical trials conducted in 2008-2019 and various factors lowering the enrollment success rate. METHODS This is a cross-sectional study with clinical trial information from the largest registration database ClinicalTrials.gov. Enrollment success rate was defined as actual enrollment greater or equal to 85% of the estimated enrollment goal. The association between trial characteristics and enrollment success was evaluated using the multivariable logistic regression. RESULTS A total of 4,004 trials in breast, lung, and colorectal cancers were included. The overall enrollment success rate was 49.1%. Compared with 2008-2010 (51.5%) and 2011-2013 (52.1%), the enrollment success rate is lower in 2014-2016 (46.5%) and 2017-2019 (36.4%). Regression analyses found trial activation year, phase I, phase I/phase II, and phase II (v phase III), sponsor agency of government (v industry), not requiring healthy volunteers, and estimated enrollment of 50-100, 100-200, 200, and >500 (v 0-50) were associated with a lower enrollment success rate (P < .05). However, trials with placebo comparator, ≥5 locations (v 1 location), and a higher number of secondary end points (eg, ≥5 v 0) were associated with a higher enrollment success rate (P < .05). The AUC for prediction of the final logistic regression models for all trials and specific trial groups ranged from 0.69 to 0.76. CONCLUSION This large-scale study supports a lower enrollment success rate over years in cancer clinical trials. Identified factors for enrollment success can be used to develop and improve recruitment strategies for future cancer trials.
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Affiliation(s)
- Siqi Zhang
- Duke Cancer Institute, Duke University, Durham, NC
- Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jianrong Zhang
- Centre for Cancer Research & Department of General Practice and Primary Care, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
| | - Sida Liu
- Department of Statistics, Florida State University, Tallahassee, FL
| | - Herbert Pang
- Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC
| | - Thomas E. Stinchcombe
- Duke Cancer Institute, Duke University, Durham, NC
- Duke University Medical Center, Durham, NC
| | - Xiaofei Wang
- Duke Cancer Institute, Duke University, Durham, NC
- Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC
- Alliance Statistics and Data Management Center, Duke University, Durham, NC
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3
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Idnay B, Fang Y, Butler A, Moran J, Li Z, Lee J, Ta C, Liu C, Yuan C, Chen H, Stanley E, Hripcsak G, Larson E, Marder K, Chung W, Ruotolo B, Weng C. Uncovering key clinical trial features influencing recruitment. J Clin Transl Sci 2023; 7:e199. [PMID: 37830010 PMCID: PMC10565197 DOI: 10.1017/cts.2023.623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 10/14/2023] Open
Abstract
Background Randomized clinical trials (RCT) are the foundation for medical advances, but participant recruitment remains a persistent barrier to their success. This retrospective data analysis aims to (1) identify clinical trial features associated with successful participant recruitment measured by accrual percentage and (2) compare the characteristics of the RCTs by assessing the most and least successful recruitment, which are indicated by varying thresholds of accrual percentage such as ≥ 90% vs ≤ 10%, ≥ 80% vs ≤ 20%, and ≥ 70% vs ≤ 30%. Methods Data from the internal research registry at Columbia University Irving Medical Center and Aggregated Analysis of ClinicalTrials.gov were collected for 393 randomized interventional treatment studies closed to further enrollment. We compared two regularized linear regression and six tree-based machine learning models for accrual percentage (i.e., reported accrual to date divided by the target accrual) prediction. The outperforming model and Tree SHapley Additive exPlanations were used for feature importance analysis for participant recruitment. The identified features were compared between the two subgroups. Results CatBoost regressor outperformed the others. Key features positively associated with recruitment success, as measured by accrual percentage, include government funding and compensation. Meanwhile, cancer research and non-conventional recruitment methods (e.g., websites) are negatively associated with recruitment success. Statistically significant subgroup differences (corrected p-value < .05) were found in 15 of the top 30 most important features. Conclusion This multi-source retrospective study highlighted key features influencing RCT participant recruitment, offering actionable steps for improvement, including flexible recruitment infrastructure and appropriate participant compensation.
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Affiliation(s)
- Betina Idnay
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Yilu Fang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Alex Butler
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Joyce Moran
- Department of Neurology, Columbia University Irving Medical Center, NY Research, New York, NY, USA
| | - Ziran Li
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Junghwan Lee
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Casey Ta
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Chi Yuan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Huanyao Chen
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Edward Stanley
- Compliance Applications, Information Technology, Columbia University, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Elaine Larson
- School of Nursing, Columbia University Irving Medical Center, New York, NY, USA
- New York Academy of Medicine, New York, NY, USA
| | - Karen Marder
- Department of Neurology, Columbia University Irving Medical Center, NY Research, New York, NY, USA
| | - Wendy Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Brenda Ruotolo
- Institutional Review Board for Human Subjects Research, Columbia University, New York, NY, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
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Idnay B, Butler A, Fang Y, Li Z, Lee J, Ta C, Liu C, Ruotolo B, Yuan C, Chen H, Hripcsak G, Larson E, Weng C. Principal Investigators' Perceptions on Factors Associated with Successful Recruitment in Clinical Trials. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2023; 2023:281-290. [PMID: 37350899 PMCID: PMC10283115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/24/2023]
Abstract
Participant recruitment continues to be a challenge to the success of randomized controlled trials, resulting in increased costs, extended trial timelines and delayed treatment availability. Literature provides evidence that study design features (e.g., trial phase, study site involvement) and trial sponsor are significantly associated with recruitment success. Principal investigators oversee the conduct of clinical trials, including recruitment. Through a cross-sectional survey and a thematic analysis of free-text responses, we assessed the perceptions of sixteen principal investigators regarding success factors for participant recruitment. Study site involvement and funding source do not necessarily make recruitment easier or more challenging from the perspective of the principal investigators. The most commonly used recruitment strategies are also the most effort inefficient (e.g., in-person recruitment, reviewing the electronic medical records for prescreening). Finally, we recommended actionable steps, such as improving staff support and leveraging informatics-driven approaches, to allow clinical researchers to enhance participant recruitment.
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Affiliation(s)
| | | | - Yilu Fang
- Department of Biomedical Informatics
| | - Ziran Li
- Department of Biomedical Informatics
| | | | - Casey Ta
- Department of Biomedical Informatics
| | - Cong Liu
- Department of Biomedical Informatics
| | | | - Chi Yuan
- Department of Biomedical Informatics
| | | | | | - Elaine Larson
- 3School of Nursing, Columbia University, New York, NY
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Li H, Luo Q, Zhang H, Ma X, Gu Z, Gong Q, Luo K. Nanomedicine embraces cancer radio-immunotherapy: mechanism, design, recent advances, and clinical translation. Chem Soc Rev 2023; 52:47-96. [PMID: 36427082 DOI: 10.1039/d2cs00437b] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Cancer radio-immunotherapy, integrating external/internal radiation therapy with immuno-oncology treatments, emerges in the current management of cancer. A growing number of pre-clinical studies and clinical trials have recently validated the synergistic antitumor effect of radio-immunotherapy, far beyond the "abscopal effect", but it suffers from a low response rate and toxicity issues. To this end, nanomedicines with an optimized design have been introduced to improve cancer radio-immunotherapy. Specifically, these nanomedicines are elegantly prepared by incorporating tumor antigens, immuno- or radio-regulators, or biomarker-specific imaging agents into the corresponding optimized nanoformulations. Moreover, they contribute to inducing various biological effects, such as generating in situ vaccination, promoting immunogenic cell death, overcoming radiation resistance, reversing immunosuppression, as well as pre-stratifying patients and assessing therapeutic response or therapy-induced toxicity. Overall, this review aims to provide a comprehensive landscape of nanomedicine-assisted radio-immunotherapy. The underlying working principles and the corresponding design strategies for these nanomedicines are elaborated by following the concept of "from bench to clinic". Their state-of-the-art applications, concerns over their clinical translation, along with perspectives are covered.
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Affiliation(s)
- Haonan Li
- Department of Radiology, Department of Biotherapy, Huaxi MR Research Center (HMRRC), Cancer Center, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China.
| | - Qiang Luo
- Department of Radiology, Department of Biotherapy, Huaxi MR Research Center (HMRRC), Cancer Center, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China.
| | - Hu Zhang
- Amgen Bioprocessing Centre, Keck Graduate Institute, Claremont, CA 91711, USA
| | - Xuelei Ma
- Department of Radiology, Department of Biotherapy, Huaxi MR Research Center (HMRRC), Cancer Center, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China.
| | - Zhongwei Gu
- Department of Radiology, Department of Biotherapy, Huaxi MR Research Center (HMRRC), Cancer Center, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China.
| | - Qiyong Gong
- Department of Radiology, Department of Biotherapy, Huaxi MR Research Center (HMRRC), Cancer Center, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China. .,Functional and Molecular Imaging Key Laboratory of Sichuan Province and Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Kui Luo
- Department of Radiology, Department of Biotherapy, Huaxi MR Research Center (HMRRC), Cancer Center, Frontiers Science Center for Disease-Related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China. .,Functional and Molecular Imaging Key Laboratory of Sichuan Province and Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
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6
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Zhang Z, Yin J, Yue Y, Su Y, Jiang H. Assessing clinical trial failure risk factors and reasons in gastric cancer. BMC Gastroenterol 2022; 22:496. [PMID: 36451088 PMCID: PMC9713972 DOI: 10.1186/s12876-022-02592-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 11/23/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Gastric cancer is one of the leading cancer-related death causes. Enormous efforts have been focused on this field in these years. However, clinical trial failure is becoming a massive obstacle for researchers to apply their research results for clinical use. This study aimed to analyze the reasons behind clinical failures and identify potential risk factors of clinical trial failures. METHODS On December, 1, 2021, we queried ClinicalTrials.gov for gastric cancer listed in phase II/III. We included trials specifying their interests in "stomach cancer", "Stomach Neoplasms", "Gastric Cancer", "Gastric Neoplasms", "Gastric Carcinoma", "Stomach Carcinoma", "Gastroesophageal Junction Cancer". Exclude criteria are: (1) Trials that start prior to 01/01/2007 and start after 12/01/2020; (2) Trials with "not yet recruiting", "suspended", "withdrawn", or "unknown" status; (3) Trials do not provide an anticipated accrual number or a start date. RESULTS A total of 567 trials are included. 10.2% of these trials are failed. 16 (2.82%) were terminated for good reasons, and 42 (7.41%) were terminated for bad reasons. Multi-centre (P-value = 0.088) and anticipated accrual (P-value = 0.099) are potential risk factors for clinical failures in the simple logistic regression model. After considering the interaction between multi-centre and anticipated accrual, the odds ratio of anticipated accrual is 0.60 (P-value = 0.009) in single centre trials. In multi-centre trials, the odds ratio of anticipated accrual is 0.72 (P-value = 0.025). The primary reason for gastric cancer trial terminations is recruitment failure. CONCLUSION The rate that trials terminated in gastric cancer has decreased compared to previous studies. Comparing to other types of oncology trials, poor accrual continues to be the predominant reason, followed by business or sponsor reasons. Single-center trials with smaller anticipated accrual number are more likely to be terminated which may resulted by limited resources invested to the trial. Single-center design exacerbated the difficulty of participant recruitment. Future studies need to continue tracking the rate of trial termination across oncology and whether the reasons behind them have changed.
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Affiliation(s)
- Zikai Zhang
- grid.24516.340000000123704535Department of Science, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200092 China
| | - Junyi Yin
- grid.24516.340000000123704535Department of Oncology, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200092 China
| | - Yang Yue
- grid.1008.90000 0001 2179 088XSchool of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010 Australia
| | - Yang Su
- grid.24516.340000000123704535Department of Oncology, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200092 China
| | - Hong Jiang
- Department of Oncology, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200092, China.
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Gerber DE, Singh H, Larkins E, Ferris A, Forde PM, Selig W, Roy UB. A New Approach to Simplifying and Harmonizing Cancer Clinical Trials-Standardizing Eligibility Criteria. JAMA Oncol 2022; 8:1333-1339. [PMID: 35925576 PMCID: PMC9934063 DOI: 10.1001/jamaoncol.2022.1664] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Importance Clinical trial sponsors rely on eligibility criteria to control the characteristics of patients in their studies, promote the safety of participants, and optimize the interpretation of results. However, in recent years, complex and often overly restrictive inclusion and exclusion criteria have created substantial barriers to patient access to novel therapies, hindered trial recruitment and completion, and limited generalizability of trial results. A LUNGevity Foundation working group developed a framework for lung cancer clinical trial eligibility criteria. The goals of this framework are to (1) simplify eligibility criteria, (2) facilitate stakeholders' (patients, clinicians, and sponsors) search for appropriate trials, and (3) harmonize trial populations to support intertrial comparisons of treatment effects. Observations Clinicians and representatives from the pharmaceutical industry, the National Cancer Institute, the US Food and Drug Administration (FDA), the European Medicines Agency, and the LUNGevity Foundation undertook a process to identify and prioritize key items for inclusion in trial eligibility criteria. The group generated a prioritized library of terms to guide investigators and sponsors in the design of first-line, advanced non-small cell lung cancer clinical trials intended to support marketing application. These recommendations address disease stage and histologic features, enrollment biomarkers, performance status, organ function, brain metastases, and comorbidities. This effort forms the basis for a forthcoming FDA draft guidance for industry. Conclusions and Relevance As an initial step, the recommended cross-trial standardization of eligibility criteria may harmonize trial populations. Going forward, by connecting diverse stakeholders and providing formal opportunity for public input, the emerging FDA draft guidance may also provide an opportunity to revise and simplify long-standing approaches to trial eligibility. This work serves as a prototype for similar efforts now underway for other cancers.
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Affiliation(s)
- David E. Gerber
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas USA
| | - Harpreet Singh
- Food and Drug Administration, Silver Spring, Maryland USA
| | - Erin Larkins
- Food and Drug Administration, Silver Spring, Maryland USA
| | | | - Patrick M. Forde
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland USA
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8
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Black MD, Esene L, McClelland R, Mayer H, Welch S, Bauman G, Vandenberg T. An Electronic Information Kiosk for Enhancing Patient Accrual for Cancer Clinical Trials: A Pilot and Feasibility Study. Cureus 2022; 14:e25114. [PMID: 35733492 PMCID: PMC9205538 DOI: 10.7759/cureus.25114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 05/07/2022] [Indexed: 11/21/2022] Open
Abstract
Introduction Low accrual to clinical trials for solid tumors at our institution led to a review of possible modifiable factors within our control. This led to a pilot project to determine whether improved patient awareness could alter accrual rates to active trials. Methods An information kiosk was located at the patient library on the ground floor of the London Regional Cancer Program. Adult cancer patients were invited to learn more about clinical trials from our research navigator, including specific trials open in our center, and to participate in the study, which involved a brief satisfaction and demographics survey. Results Three hundred and eighty-six (386) patients interacted with the clinical trial information kiosk over the eight weeks it was open. Of these, 32 patients consented and filled out surveys, which indicated an overall positive interaction with the kiosk. Unfortunately, in the time period examined, clinical trial accrual rates appeared to decrease when the pre- and post-kiosk activation periods were compared (44 versus 37 patients accrued to various trials). Conclusion Our pilot study found that the implementation of a clinical trial information kiosk was easy to understand and useful for patients to learn more about clinical trials. Barriers to this patient satisfaction translating into increased accrual rates in our center included suboptimal kiosk location and lack of guidance to the kiosk from clerical staff. High patient satisfaction scores support the potential value of permanent clinical trial information kiosks in our cancer center, but this requires increased attention to visibility, location, and staff education.
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Versteijne E, Suker M, Groen JV, Besselink MG, Bonsing BA, Bosscha K, Busch OR, de Hingh IHJT, de Jong KP, Molenaar IQ, van Santvoort HC, Verkooijen HM, Van Eijck CH, van Tienhoven G. External Validity of the Multicenter Randomized PREOPANC Trial on Neoadjuvant Chemoradiotherapy in Pancreatic Cancer: Outcome of Eligible but Nonrandomized Patients. Ann Surg 2022; 275:972-978. [PMID: 33273349 DOI: 10.1097/sla.0000000000004364] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVES To investigate the accrual proportion and patients' reasons for not participating in the PREOPANC trial on neoadjuvant chemoradiotherapy versus immediate surgery in resectable and borderline resectable pancreatic cancer, and to compare these patients' outcomes with those of patients who had been randomized in the trial. SUMMARY OF BACKGROUND DATA The external validity of multicenter randomized trials in cancer treatment has been criticized for suboptimal non-representative inclusion. In trials, it is unclear how outcomes compare between randomized and nonrandomized patients. METHODS At 8 of 16 participant centers, this multicenter observational study identified validation patients, who had been eligible but not randomized during recruitment for the PREOPANC trial. We assessed the accrual proportion, investigated their most common reasons for not participating in the trial, and compared resection rates, radical (R0) resection rates, and overall survival between the validation patients and PREOPANC patients, who had been randomized in the trial to immediate surgery. RESULTS In total, 455 patients had been eligible during the recruitment period, 151 of whom (33%) had been randomized. Fifty-five percent of the 304 validation patients had refused to participate. Median overall survival in the validation group was 15.2 months, against 15.5 months in the PREOPANC group (P = 1.00). The respective resection rates (76% vs 73%) and R0 resection rates (51% vs 46%) did not differ between the groups. CONCLUSIONS The PREOPANC trial included a reasonable percentage of 33% of eligible patients. In terms of the outcomes survival, resection rate, and R0 resection rate, this appeared to be a representative group.
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Affiliation(s)
- Eva Versteijne
- Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Mustafa Suker
- Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Jesse V Groen
- Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Marc G Besselink
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bert A Bonsing
- Department of Surgery, Leiden University Medical Center, Leiden, the Netherlands
| | - Koop Bosscha
- Department of Surgery, Jeroen Bosch Hospital, Den Bosch, the Netherlands
| | - Olivier R Busch
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Koert P de Jong
- Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - I Quintus Molenaar
- Department of Surgery, RAKU, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - Helena M Verkooijen
- Imaging Division, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Casper H Van Eijck
- Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Geertjan van Tienhoven
- Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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Sampson R, Shapiro S, He W, Denmark S, Kirchoff K, Hutson K, Paranal R, Forney L, McGhee K, Harvey J. An integrated approach to improve clinical trial efficiency: Linking a clinical trial management system into the Research Integrated Network of Systems. J Clin Transl Sci 2022; 6:e63. [PMID: 35720964 PMCID: PMC9161043 DOI: 10.1017/cts.2022.382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 03/25/2022] [Accepted: 03/28/2022] [Indexed: 12/04/2022] Open
Abstract
Low-accruing clinical trials delay translation of research breakthroughs into the clinic, expose participants to risk without providing meaningful clinical insight, increase the cost of therapies, and waste limited resources. By tracking patient accrual, Clinical and Translational Science Awards hubs can identify at-risk studies and provide them the support needed to reach recruitment goals and maintain financial solvency. However, tracking accrual has proved challenging because relevant patient- and protocol-level data often reside in siloed systems. To address this fragmentation, in September 2020 the South Carolina Clinical and Translational Research Institute, with an academic home at the Medical University of South Carolina, implemented a clinical trial management system (CTMS), with its access to patient-level data, and incorporated it into its Research Integrated Network of Systems (RINS), which links study-level data across disparate systems relevant to clinical research. Within the first year of CTMS implementation, 324 protocols were funneled through CTMS/RINS, with more than 2600 participants enrolled. Integrated data from CTMS/RINS have enabled near-real-time assessment of patient accrual and accelerated reimbursement from industry sponsors. For institutions with bioinformatics or programming capacity, the CTMS/RINS integration provides a powerful model for tracking and improving clinical trial efficiency, compliance, and cost-effectiveness.
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Affiliation(s)
- Royce Sampson
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Office of Clinical Research, Office of the Vice President for Research, Medical University of South Carolina, Charleston, SC, USA
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Steve Shapiro
- Office of Clinical Research, Office of the Vice President for Research, Medical University of South Carolina, Charleston, SC, USA
| | - Wenjun He
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
| | - Signe Denmark
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Office of Clinical Research, Office of the Vice President for Research, Medical University of South Carolina, Charleston, SC, USA
| | - Katie Kirchoff
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, USA
| | - Kyle Hutson
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Office of Clinical Research, Office of the Vice President for Research, Medical University of South Carolina, Charleston, SC, USA
| | - Rechelle Paranal
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
| | - Leila Forney
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Office of Clinical Research, Office of the Vice President for Research, Medical University of South Carolina, Charleston, SC, USA
| | - Kimberly McGhee
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Academic Affairs Faculty, Medical University of South Carolina, Charleston, SC, USA
| | - Jillian Harvey
- South Carolina Clinical & Translational Research Institute, Medical University of South Carolina, Charleston, SC, USA
- Department of Healthcare Leadership and Management, Medical University of South Carolina, Charleston, SC, USA
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11
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Tang F, Gajewski BJ. Comparative Effectiveness Research using Bayesian Adaptive Designs for Rare Diseases: Response Adaptive Randomization Reusing Participants. Stat Biopharm Res 2021; 15:154-163. [PMID: 36875290 PMCID: PMC9979780 DOI: 10.1080/19466315.2021.1961854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 04/23/2021] [Accepted: 07/08/2021] [Indexed: 10/20/2022]
Abstract
Slow accrual rate is a major challenge in clinical trials for rare diseases and is identified as the most frequent reason for clinical trials to fail. This challenge is amplified in comparative effectiveness research where multiple treatments are compared to identify the best treatment. Novel efficient clinical trial designs are in urgent need in these areas. Our proposed response adaptive randomization (RAR) reusing participants trial design mimics the real-world clinical practice that allows patients to switch treatments when desired outcome is not achieved. The proposed design increases efficiency by two strategies: 1) Allowing participants to switch treatments so that each participant can have more than one observation and hence it is possible to control for participant specific variability to increase statistical power; and 2) Utilizing RAR to allocate more participants to the promising arms such that ethical and efficient studies will be achieved. Extensive simulations were conducted and showed that, compared with trials where each participant receives one treatment, the proposed participants reusing RAR design can achieve comparable power with a smaller sample size and a shorter trial duration, especially when the accrual rate is low. The efficiency gain decreases as the accrual rate increases.
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Affiliation(s)
- Fengming Tang
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160
- Saint Luke’s Health System, Kansas City, MO, 64111
| | - Byron J. Gajewski
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, 66160
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12
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Giantonio BJ. Eligibility in Cancer Clinical Research: The Intersection of Discovery, Generalizability, Beneficence, and Justice. Clin Cancer Res 2021; 27:2369-2371. [PMID: 33602680 DOI: 10.1158/1078-0432.ccr-21-0085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 02/09/2021] [Accepted: 02/15/2021] [Indexed: 11/16/2022]
Abstract
Eligibility criteria in clinical trials limit the study population for safety and scientific purposes. The American Society of Clinical Oncology and The Friends of Cancer Research collaboration reconsidered common eligibility criteria in cancer trials and found many to be unnecessarily restrictive. The current recommendations further their efforts to facilitate accrual and improve the generalizability of research results to practice.See related articles, p. 2394, 2400, 2408, 2416, 2424, and 2430.
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Affiliation(s)
- Bruce J Giantonio
- Division of Hematology and Oncology, Massachusetts General Hospital, Boston, Massachusetts.
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13
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Peters GW, Tao W, Wei W, Miccio JA, Jethwa KR, Cecchini M, Johung KL. Publication Bias in Gastrointestinal Oncology Trials Performed over the Past Decade. Oncologist 2021; 26:660-667. [PMID: 33728733 DOI: 10.1002/onco.13759] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 02/26/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Randomized controlled trials (RCTs) are the gold standard for evidence-based practice, but their development and implementation is resource intensive. We aimed to describe modern RCTs in gastrointestinal (GI) cancer and identify predictors of successful accrual and publication. MATERIALS AND METHODS ClinicalTrials.gov was queried for phase III GI cancer RCTs opened between 2010 and 2019 and divided into two cohorts: past and recruiting. Past trials were analyzed for predictors of successful accrual and the subset with ≥3 years follow-up were analyzed for predictors of publication. Univariate and multivariable (MVA) logistic regression were used to identify covariates associated with complete accrual and publication status. RESULTS A total of 533 GI RCTs were opened from 2010 to 2019, 244 of which are still recruiting. In the "past" trials cohort (235/533) MVA, Asian continent of enrollment was a predictor for successful accrual, whereas trials with prolonged enrollment (duration longer than median of 960 days) trended to failed accrual. Predictors for publication on MVA included international enrollment and accrual completion. Sponsorship was not associated with accrual or publication. Notably, 33% of past trials remain unpublished, and 60% of trials that were closed early remain unpublished. CONCLUSION Accrual rate and the primary continent of enrollment drive both trial completion and publication in GI oncology. Accrual must be streamlined to enhance the impact of RCTs on clinical management. A large portion of trials remain unpublished, underscoring the need to encourage dissemination of all trials to, at a minimum, inform future trial design. IMPLICATIONS FOR PRACTICE Two-thirds of gastrointestinal (GI) oncology phase III randomized controlled trials successfully accrue; however, one third of these trials are unpublished and more than half of trials that close early are unpublished. The strongest predictors for publication are successful accrual and international collaborations. Initiatives to optimize the trial enrollment process need to be explored to maximize the potential for trials to engender progress in clinical practice. Moreover, this study identified a significant publication bias in the realm of GI oncology, and the field should promote reporting of all trials in order to better inform future trial questions and design.
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Affiliation(s)
- Gabrielle W Peters
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Weiwei Tao
- Department of Mechanical Engineering, Boston University, Boston, Massachusetts, USA
| | - Wei Wei
- Yale School of Public Health, New Haven, Connecticut, USA
| | - Joseph A Miccio
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Krishan R Jethwa
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Michael Cecchini
- Department of Internal Medicine (Medical Oncology), Yale School of Medicine, New Haven, Connecticut, USA
| | - Kimberly L Johung
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut, USA
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14
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Pasalic D, Tang C, Jagsi R, Fuller CD, Koong AC, Ludmir EB. Association of Industry Sponsorship With Cancer Clinical Trial Accrual. JAMA Oncol 2021; 6:1625-1627. [PMID: 32815984 DOI: 10.1001/jamaoncol.2020.1284] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Dario Pasalic
- The University of Texas MD Anderson Cancer Center, Houston
| | - Chad Tang
- The University of Texas MD Anderson Cancer Center, Houston
| | | | - C David Fuller
- The University of Texas MD Anderson Cancer Center, Houston
| | - Albert C Koong
- The University of Texas MD Anderson Cancer Center, Houston
| | - Ethan B Ludmir
- The University of Texas MD Anderson Cancer Center, Houston
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15
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Stensland K, Kaffenberger S, Canes D, Galsky M, Skolarus T, Moinzadeh A. Assessing Genitourinary Cancer Clinical Trial Accrual Sufficiency Using Archived Trial Data. JCO Clin Cancer Inform 2020; 4:614-622. [DOI: 10.1200/cci.20.00031] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
PURPOSE Clinical trials often fail to reach their anticipated end points, most frequently because of poor accrual. Prior studies have analyzed trial termination, but it has not been easy to assess accrual estimates using international databases such as ClinicalTrials.gov because of limitations in accessing accrual information. Specifically, it is not easy to extract both anticipated and actual accrual of clinical trials. We designed a new algorithmic approach to extracting trial accrual data from ClinicalTrials.gov and used it to estimate the sufficiency of patient accrual onto genitourinary (GU) cancer trials. METHODS We queried ClinicalTrials.gov for completed/terminated phase II and III clinical trials for prostate, bladder, kidney, testicular, and ureteral cancers registered after 2007. We extracted trial characteristics from available XML files. We then used a Python algorithm to access prior trial registrations on the ClinicalTrials.gov archive site and extract both anticipated and actual accrual numbers. We then compared the actual accrual of each trial to its anticipated accrual and defined sufficient accrual as 85% of anticipated accrual. RESULTS The algorithm was 100% accurate compared with hand extraction in a small validation subset. A total of 925 trials were included, of which 840 (91%) had both anticipated and actual accrual. Only 418 (50%) trials had sufficient accrual (≥ 85% of anticipated). Considering only trials marked as successfully completed, 395/597 (66%) reached sufficient accrual. CONCLUSION GU cancer trials often do not meet their anticipated accrual goals. New approaches to trial conduct are direly needed. Our reproducible and scalable approach to extracting accrual information can be applied to analysis of ClinicalTrials.gov in future analyses in the hope of improving the efficiency of the clinical trials enterprise.
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Affiliation(s)
| | | | - David Canes
- Lahey Hospital and Medical Center, Burlington, MA
| | - Matthew Galsky
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY
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16
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Frumovitz M, Westin SN, Salvo G, Zarifa A, Xu M, Yap TA, Rodon AJ, Karp DD, Abonofal A, Jazaeri AA, Naing A. Phase II study of pembrolizumab efficacy and safety in women with recurrent small cell neuroendocrine carcinoma of the lower genital tract. Gynecol Oncol 2020; 158:570-575. [PMID: 32534809 PMCID: PMC7486997 DOI: 10.1016/j.ygyno.2020.05.682] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 05/31/2020] [Indexed: 12/19/2022]
Abstract
OBJECTIVE To investigate the efficacy and safety of pembrolizumab in women with recurrent small cell neuroendocrine tumors of the lower genital tract. METHODS We conducted an open-label, investigator-initiated phase II basket trial of pembrolizumab 200 mg intravenously every 3 weeks in patients with rare tumors (ClinicalTrials.gov: NCT02721732). The trial had prespecified cohorts, including small cell malignancies of extrapulmonary origin. Eligibility criteria included disease progression during standard treatment in the 6 months before study enrollment. Patients were enrolled from February 2017 to February 2019. The primary endpoint was the proportion of patients alive without progression at 27 weeks. Response to pembrolizumab was evaluated every 9 weeks (3 cycles) with radiographic imaging. RESULTS Seven women with gynecologic extrapulmonary small cell carcinoma were enrolled, 6 with cervical and 1 with vulvar carcinoma. No patient was progression free at 27 weeks. At first radiologic assessment, 1 patient had stable disease, while 6 had progression. The single patient with stable disease at 6 weeks had disease progression at 14 weeks. The median progression-free interval was 2.1 months (range 0.8-3.3 months). Severe treatment-related adverse events (≥grade 3) were seen in 2 of 7 patients (29%); 1 patient had grade 3 asymptomatic elevation of serum alkaline phosphatase, and 1 had grade 3 asymptomatic elevation of serum alanine aminotransferase. CONCLUSIONS Pembrolizumab alone showed minimal activity in women with recurrent small cell neuroendocrine tumors of the lower genital tract. Treatment was well tolerated in the majority of study participants, and the rate of severe adverse events was low.
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Affiliation(s)
- Michael Frumovitz
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Shannon N Westin
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Gloria Salvo
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Abdulrazzak Zarifa
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Mingxuan Xu
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Timothy A Yap
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Ahnert J Rodon
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Daniel D Karp
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Abdulrahman Abonofal
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States
| | - Amir A Jazaeri
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
| | - Aung Naing
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
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17
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Krutsinger DC, O’Leary KL, Ellenberg SS, Cotner CE, Halpern SD, Courtright KR. A Randomized Controlled Trial of Behavioral Nudges to Improve Enrollment in Critical Care Trials. Ann Am Thorac Soc 2020; 17:1117-1125. [PMID: 32441987 PMCID: PMC7462327 DOI: 10.1513/annalsats.202003-194oc] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 05/21/2020] [Indexed: 01/04/2023] Open
Abstract
Rationale: Low and slow patient enrollment remains a barrier to critical care randomized controlled trials (RCTs). Behavioral economic insights suggest that nudges may address some enrollment challenges.Objectives: To evaluate the efficacy of a novel preconsent survey consisting of nudges on critical care RCT enrollment.Methods: We conducted an RCT in 10 intensive care units (ICUs) among surrogate decision-makers (SDMs). The novel multicomponent behavioral nudge survey was administered immediately before soliciting SDMs' informed consent for their patients' participation in a sham trial of two mechanical ventilation weaning approaches in acute respiratory failure. The primary outcome was the enrollment rate for the sham trial. Secondary outcomes included undue and unjust inducements. We also explored SDM and patient predictors of enrollment using multivariate regression.Results: Among 182 SDMs, 93 were randomized to receive the intervention survey and 89 to receive standard informed consent. There was no statistically significant difference in enrollment rates between the intervention (29%) and standard consent (34%) groups (percentage difference, 5%; 95% confidence interval [CI], -9% to 18%; P = 0.50). There was no evidence of undue or unjust inducement. White SDMs were more likely to enroll the patient compared with non-white SDMs (odds ratio, 3.7; 95% CI, 1.1 to 12.2; P = 0.03). SDMs who perceived a higher risk of participation were less likely to enroll the patient (odds ratio, 0.57; 95% CI, 0.46 to 0.71; P < 0.001).Conclusions: A preconsent behavioral nudge survey among SDMs of patients with acute respiratory failure in the ICU did not increase enrollment rates for a sham RCT compared with standard informed consent procedures.Clinical trial registered with ClinicalTrials.gov (NCT03284359).
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Affiliation(s)
- Dustin C. Krutsinger
- Division of Pulmonary, Critical Care, and Sleep Medicine, University of Nebraska Medical Center, Omaha, Nebraska
| | | | | | | | - Scott D. Halpern
- Department of Biostatistics, Epidemiology, and Informatics
- Palliative and Advanced Illness Research Center
- Fostering Improvement in End-of-Life Decision Science Program
- Center for Health Incentives and Behavioral Economics
- Leonard Davis Institute of Health Economics, and
- Division of Pulmonary, Allergy, and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
| | - Katherine R. Courtright
- Palliative and Advanced Illness Research Center
- Fostering Improvement in End-of-Life Decision Science Program
- Center for Health Incentives and Behavioral Economics
- Leonard Davis Institute of Health Economics, and
- Division of Pulmonary, Allergy, and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; and
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18
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The influence of race and socioeconomic status on therapeutic clinical trial screening and enrollment. J Neurooncol 2020; 148:131-139. [DOI: 10.1007/s11060-020-03503-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 04/17/2020] [Indexed: 10/24/2022]
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19
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Wong AR, Sun V, George K, Liu J, Padam S, Chen BA, George T, Amini A, Li D, Sedrak MS. Barriers to Participation in Therapeutic Clinical Trials as Perceived by Community Oncologists. JCO Oncol Pract 2020; 16:e849-e858. [PMID: 32240068 DOI: 10.1200/jop.19.00662] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
PURPOSE Despite considerable research on the barriers to enrollment in cancer therapeutic trials, few studies have elicited barriers from the perspective of community physicians, who provide the majority of cancer care. The purpose of this study was to characterize barriers to and facilitators of cancer therapeutic trials as perceived by oncologists in community practices. METHODS Twenty semistructured interviews were conducted with oncologists at six community sites affiliated with City of Hope National Medical Center from March to June 2018. Responses were recorded digitally and transcribed. Data were analyzed using qualitative content analysis. RESULTS Of the 20 participants, 4 (20%) were women, 13 (65%) had > 10 years of practice experience, and 16 (80%) reported that < 5% of their patients were enrolled in a therapeutic trial. Participants identified four system-level barriers: lack of appropriate trials for community-based settings, insufficient infrastructure support, restrictive eligibility criteria, and financial limitations; three physician-level barriers: lack of awareness of available trials, lack of knowledge of trial details, and lack of time; and two patient-level barriers: patient burden and negative beliefs/attitudes toward research. Efforts aimed to increase trial availability, clinical trial support personnel, and physician knowledge were identified as major facilitators. CONCLUSION Community oncologists face numerous complex, multifaceted barriers to cancer therapeutic trial enrollment. Although expanding clinical research beyond the academic setting allows access to a larger and more diverse patient population, increasing generalizability and relevance of trial findings, there remains a substantial need for new strategies to improve cancer research delivery in the community.
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Affiliation(s)
- Andrew R Wong
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Virginia Sun
- Department of Population Science, City of Hope, Duarte, CA
| | - Kevin George
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Jennifer Liu
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Simran Padam
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Brandon A Chen
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Thomas George
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Arya Amini
- Department of Radiation Oncology, City of Hope, Duarte, CA
| | - Daneng Li
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
| | - Mina S Sedrak
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA
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20
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Iruku P, Goros M, Gelfond J, Chang J, Padalecki S, Mesa R, Kaklamani VG. Developing a model to predict accrual to cancer clinical trials: Data from an NCI designated cancer center. Contemp Clin Trials Commun 2019; 15:100421. [PMID: 31372575 PMCID: PMC6658414 DOI: 10.1016/j.conctc.2019.100421] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 07/10/2019] [Accepted: 07/18/2019] [Indexed: 11/24/2022] Open
Abstract
INTRODUCTION As cancer center funds are allocated toward several resources, clinical trial offices and the clinical trial infrastructure is constantly scrutinized. It has been shown that 20% of clinical trials fail to achieve their accrual goal and in an institutional level several trials are open with poor accrual. We sought to identify factors that are associated with clinical trial accrual and develop a model to predict clinical trial accrual. METHODS AND MATERIAL We identified all clinical trials from 1999 to 2015 at UT Health Cancer Center San Antonio. We included observational as well as interventional clinical trials. We collected several variables such as type of study, type of malignancy, trial phase, PI of study. RESULTS In total we included 297 clinical trials. We identified several factors to be associated with clinical trial accrual (Sponsor type, trial phase, disease category, type of trial, disease state and whether the trial involved a new investigational agent). We developed a predictive model with an AUC of 0.65 that showed that observational, interventional, industry-sponsored trials and trials authored by the local PI were more likely to achieve their accrual goal. CONCLUSION We were able to identify several factors that were significantly associated with clinical trial accrual. Based on these factors we developed a prediction model for clinical trial accrual. We believe that use of this model can help improve our cancer centers clinical trial portfolio and help in fund allocation.
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Affiliation(s)
- Praveena Iruku
- Department of Hematology/Oncology, University of Colorado Health, Colorado Springs, CO, USA
| | - Martin Goros
- Department of Epidemiology and Biostatistics, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Jonathan Gelfond
- Department of Epidemiology and Biostatistics, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Jenny Chang
- Houston Methodist Cancer Center, Houston, TX, USA
| | - Susan Padalecki
- Department of Medicine, UT Health Cancer Center San Antonio, San Antonio, TX, USA
| | - Ruben Mesa
- Department of Medicine, UT Health Cancer Center San Antonio, San Antonio, TX, USA
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21
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Gal J, Milano G, Ferrero JM, Saâda-Bouzid E, Viotti J, Chabaud S, Gougis P, Le Tourneau C, Schiappa R, Paquet A, Chamorey E. Optimizing drug development in oncology by clinical trial simulation: Why and how? Brief Bioinform 2019; 19:1203-1217. [PMID: 28575140 DOI: 10.1093/bib/bbx055] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Indexed: 12/11/2022] Open
Abstract
In therapeutic research, the safety and efficacy of pharmaceutical products are necessarily tested on humans via clinical trials after an extensive and expensive preclinical development period. Methodologies such as computer modeling and clinical trial simulation (CTS) might represent a valuable option to reduce animal and human assays. The relevance of these methods is well recognized in pharmacokinetics and pharmacodynamics from the preclinical phase to postmarketing. However, they are barely used and are poorly regarded for drug approval, despite Food and Drug Administration and European Medicines Agency recommendations. The generalization of CTS could be greatly facilitated by the availability of software for modeling biological systems, by clinical trial studies and hospital databases. Data sharing and data merging raise legal, policy and technical issues that will need to be addressed. Development of future molecules will have to use CTS for faster development and thus enable better patient management. Drug activity modeling coupled with disease modeling, optimal use of medical data and increased computing speed should allow this leap forward. The realization of CTS requires not only bioinformatics tools to allow interconnection and global integration of all clinical data but also a universal legal framework to protect the privacy of every patient. While recognizing that CTS can never replace 'real-life' trials, they should be implemented in future drug development schemes to provide quantitative support for decision-making. This in silico medicine opens the way to the P4 medicine: predictive, preventive, personalized and participatory.
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Affiliation(s)
- Jocelyn Gal
- Epidemiology and Biostatistics Unit at the Antoine Lacassagne Center, Nice, France
| | | | | | | | | | | | - Paul Gougis
- Pitie´-Salp^etrie`re Hospital in Paris, France
| | | | | | - Agnes Paquet
- Molecular and Cellular Pharmacology Institute of Sophia Antipolis, Valbonne, France
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22
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Krutsinger DC, Yadav KN, Cooney E, Brooks S, Halpern SD, Courtright KR. A pilot randomized trial of five financial incentive strategies to increase study enrollment and retention rates. Contemp Clin Trials Commun 2019; 15:100390. [PMID: 31431933 PMCID: PMC6580090 DOI: 10.1016/j.conctc.2019.100390] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 05/21/2019] [Accepted: 06/01/2019] [Indexed: 11/21/2022] Open
Abstract
Background Enrollment and retention difficulties remain major barriers to conducting clinical trials. Financial incentives may promote clinical trial enrollment, however delivery methods to maximize enrollment, maximize retention, and minimize cost remains uncertain. Methods We conducted a single-blind, web-based randomized controlled trial of five financial incentive strategies on enrollment and retention rates in a longitudinal study of advance directives among community-dwelling older adults. Participants were eligible to receive a fixed total financial incentive, but the disbursement amounts at each study timepoint (baseline, 2-weeks, 4-weeks, and 6-weeks) differed between study arms. At each timepoint, participants completed a different advance directive. We conducted an intention-to-treat analysis for the primary and secondary outcomes of enrollment and retention. Results 1803 adults were randomized to one of five incentive strategies: constant n = 361; increasing n = 357; U-shaped n = 361; surprise n = 360; self-select n = 364. Overall, 989 (54.9%) participants elected to enroll in the advance directive study. There were no differences in enrollment rates between the control (constant 53.5%) and any of the four intervention study arms (increasing 54.3%, p = 0.81; U-shaped 57.3%, p = 0.30; surprise 56.9%, p = 0.35; and self-select 52.2%, p = 0.73). There were no differences in retention rates between the control (constant 2.1%) and any of the four intervention study arms (increasing 5.2%, p = 0.09; U-shaped 3.9%, p = 0.23; surprise 2.4%, p = 0.54; self-select 2.1%, p = 0.63). Conclusions Financial incentive programs for trial enrollment informed by behavioral economic insights were no more effective than a constant-payment approach in this web-based pilot study.
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Affiliation(s)
- Dustin C Krutsinger
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA.,Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kuldeep N Yadav
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA
| | - Elizabeth Cooney
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA
| | - Steven Brooks
- Palliative and Advanced Illness Research Center, USA
| | - Scott D Halpern
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA.,Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katherine R Courtright
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA.,Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Krutsinger DC, McMahon J, Stephens-Shields AJ, Bayes B, Brooks S, Hitsman BL, Lubitz SF, Reyes C, Schnoll RA, Ryan Greysen S, Mercede A, Patel MS, Reale C, Barg F, Karlawish J, Polsky D, Volpp KG, Halpern SD. Randomized evaluation of trial acceptability by INcentive (RETAIN): Study protocol for two embedded randomized controlled trials. Contemp Clin Trials 2019; 76:1-8. [PMID: 30414865 PMCID: PMC6354250 DOI: 10.1016/j.cct.2018.11.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 11/02/2018] [Accepted: 11/06/2018] [Indexed: 10/27/2022]
Abstract
INTRODUCTION The most common and conceptually sound ethical concerns with financial incentives for research participation are that they may (1) represent undue inducements by blunting peoples' perceptions of research risks, thereby preventing fully informed consent; or (2) represent unjust inducements by encouraging enrollment preferentially among the poor. Neither of these concerns has been shown to manifest in studies testing the effects of incentives on decisions to participate in hypothetical randomized clinical trials (RCTs), but neither has been assessed in real RCTs. METHODS AND ANALYSES We are conducting randomized trials of real incentives embedded within two parent RCTs. In each of two trials conducted in parallel, we are randomizing 576 participants to one of three incentive groups. Following preliminary determination of patients' eligibility in the parent RCT, we assess patients' research attitudes, demographic characteristics, perceived research risks, time spent reviewing consent documents, ability to distinguish research from patient care, and comprehension of key trial features. These quantitative assessments will be supplemented by semi-structured interviews for a selected group of participants that more deeply explore patients' motivations for trial participation. The trials are each designed to have adequate power to rule out undue and unjust inducement. We are also exploring potential benefits of incentives, including possible increased attention to research risks and cost-effectiveness.
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Affiliation(s)
- Dustin C Krutsinger
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
| | - Jacqueline McMahon
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alisa J Stephens-Shields
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian Bayes
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Brooks
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian L Hitsman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Su Fen Lubitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Celine Reyes
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Robert A Schnoll
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - S Ryan Greysen
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ashley Mercede
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mitesh S Patel
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Catherine Reale
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Fran Barg
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA; Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Anthropology, University of Pennsylvania School of Arts and Sciences, Philadelphia, PA, United States
| | - Jason Karlawish
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Memory Center at the Penn Neuroscience Center, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Polsky
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin G Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Scott D Halpern
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Steensma DP, Brunner AM, DeZern AE, Garcia-Manero G, Komrokji RS, Odenike OS, Roboz GJ, Savona MR, Stone RM, Sekeres MA. Low clinical trial accrual of patients with myelodysplastic syndromes: Causes and potential solutions. Cancer 2018; 124:4601-4609. [PMID: 30289970 DOI: 10.1002/cncr.31769] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 08/03/2018] [Accepted: 08/21/2018] [Indexed: 11/11/2022]
Abstract
Despite few effective therapies, only a small percentage of patients diagnosed with myelodysplastic syndromes (MDS) in the United States are enrolled in prospective, interventional clinical trials. MDS-specific barriers to trial accrual include a high frequency of elderly patients with comorbid conditions, atypical disease features and uncertainty regarding the diagnosis (because other nonclonal processes also can cause dysplasia and cytopenias), a history of another nonmyeloid neoplasm resulting in therapy-related MDS, rapid disease recurrence after allogeneic stem cell transplantation, and an arbitrary division between MDS and acute myeloid leukemia. In addition, barriers to accrual that are common to other oncology populations, such as difficulty traveling to clinical trial enrollment sites and narrow trial eligibility criteria, also prevent patients with MDS from enrolling in studies. Collectively these barriers must be assessed systematically, and creative solutions are needed to improve outcomes for this needy patient population.
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Affiliation(s)
- David P Steensma
- Division of Hematological Malignancies, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Andrew M Brunner
- Division of Hematology and Medical Oncology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Amy E DeZern
- Division of Hematological Malignancies, Sidney Kimmel Cancer Center, Johns Hopkins University, Baltimore, Maryland
| | | | - Rami S Komrokji
- Moffitt Cancer Center, Malignant Hematology Department, Tampa, Florida
| | - Olatoyosi S Odenike
- Division of Hematology and Medical Oncology, Department of Medicine, University of Chicago, Chicago, Illinois
| | - Gail J Roboz
- Division of Hematology & Oncology, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Michael R Savona
- Division of Hematology & Oncology, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Richard M Stone
- Division of Hematological Malignancies, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Mikkael A Sekeres
- Department of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio
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25
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Drazer MW, Sweis RF. Low clinical adoption of tumor genomic profiling: cause for concern? J Med Econ 2018; 21:721-723. [PMID: 29708449 PMCID: PMC6062854 DOI: 10.1080/13696998.2018.1470978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Michael W. Drazer
- Department of Medicine, Section of Hematology/Oncology,
Comprehensive Cancer Center, University of Chicago, IL, USA
- Department of Human Genetics, University of Chicago, IL,
USA
| | - Randy F. Sweis
- Department of Medicine, Section of Hematology/Oncology,
Comprehensive Cancer Center, University of Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics,
University of Chicago, Chicago, IL, USA
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26
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Besle S, Schultz E, Hollebecque A, Varga A, Baldini C, Martin P, Postel-Vinay S, Bahleda R, Gazzah A, Michot JM, Marabelle A, Angevin E, Armand JP, Ribrag V, Soria JC, Massard C. Organisational factors influencing early clinical trials enrollment: Gustave Roussy experience. Eur J Cancer 2018; 98:17-22. [PMID: 29859337 DOI: 10.1016/j.ejca.2018.04.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 04/19/2018] [Indexed: 11/18/2022]
Abstract
PURPOSE Enrolment process influences the likelihood of patients' inclusion in early clinical trials (ECT) through social, medical and organisational factors. PATIENTS AND METHODS All patients referred from 2008 to 2016 to the Drug Development Department (DITEP) of Gustave Roussy (GR) were reviewed. Referring physician, organisational factors, medical and socioeconomic characteristics for patients were analysed. Multivariate analysis was performed with regard to those factors. A telephone survey was conducted on a sample of referring physicians located outside GR (N = 142). RESULTS Between 2008 and 2016, 8694 requests were received with 49% from external physicians. Here, 4517 were male patients with a median age of 58 [49-66] years (range 18-85). Tumour types were gastrointestinal (28%), lung (19%), breast (9%) and gynaecologic (8%). Mean enrolment rate was 37% (ranging from 24 to 45%). From 2008 to 2016, the enrolment rate decreases from 39% to 24%. In the meantime, DITEP trials portfolio evolves with the part of precision medicine trials increase from 12% to 40%. Factors that were significantly associated with a lower likelihood of being enrolled were referral from an external physician (OR 0.15 s.16-0.21]) compared to a physician from DITEP and year of the request (2.74 [1.8-2.9] 2008 versus 2016). The enrolment rate and the number of patients addressed have a high variability regarding referring physicians, which is little explained by characteristics as training, previous experience or attitude regarding ECT. CONCLUSION Beyond patients' individual characteristics, we show that organisational and professional factors have a major impact on likelihood of enrolment in ECT.
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Affiliation(s)
- Sylvain Besle
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France; Aix Marseille Univ, INSERM, IRD, SESSTIM, 232 Bd Ste Marguerite BP 156 13273 Marseille Cedex 9 France.
| | - Emilien Schultz
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France; Aix Marseille Univ, INSERM, IRD, SESSTIM, 232 Bd Ste Marguerite BP 156 13273 Marseille Cedex 9 France
| | - Antoine Hollebecque
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Andreea Varga
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Capucine Baldini
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Patricia Martin
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Sophie Postel-Vinay
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Rastislav Bahleda
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Anas Gazzah
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Jean-Marie Michot
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Aurélien Marabelle
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Eric Angevin
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Jean-Pierre Armand
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Vincent Ribrag
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Jean-Charles Soria
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
| | - Christophe Massard
- Gustave Roussy, Université Paris-Saclay, Drug Development Department (DITEP), Villejuif, F-94805, France
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27
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Lim WS, Meakin G, Brittain C, Bewick T, Duley L. Improving readiness for recruitment through simulated trial activation: the Adjuvant Steroids in Adults with Pandemic influenza (ASAP) trial. Trials 2017; 18:546. [PMID: 29145878 PMCID: PMC5693476 DOI: 10.1186/s13063-017-2290-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 10/16/2017] [Indexed: 11/21/2022] Open
Abstract
Background Research in public health emergencies requires trials to be set up in readiness for activation at short notice and in anticipation of limited timelines for patient recruitment. We conducted a simulated activation of a hibernating pandemic influenza clinical trial in order to test trial processes and to determine the value of such simulation in maintaining trial readiness. Methods The simulation involved the Nottingham Clinical Trials Unit, one participating hospital, one manufacturing unit and the Investigational Medicinal Product (IMP) supplier. During the exercise, from 15 September 2015 to 2 December 2015, clinical staff at the participating site completed the trial training package, a volunteer acting as a patient was recruited to the study, ‘dummy’ IMP was prescribed and follow-up completed. Results Successful activation of the hibernating trial with patient recruitment within 4 weeks of ‘arousal’ as planned was demonstrated. A need for greater resilience in anticipation of staff absenteeism was identified, particularly in relation to key trial procedures where the potential for delay is high. A specific issue relating to the IMP Stock Control System was highlighted as a potential source of error that could compromise the randomisation sequence. The simulation exercise was well received by site investigators and increased their confidence in being able to meet the likely demands of the trial when activated. The estimated cost of the exercise was £1995; 90% of this being staff costs. Conclusions Simulated activation is useful as a means to test, and prepare for, the rapid activation of ‘hibernating’ research studies. Whether simulation exercises can also help reduce waste in complex clinical trial research deserves further exploration. Trial registration EudraCT Number 2013-001051-12, ISRCTN72331452. Registered on 6 March 2013.
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Affiliation(s)
- Wei Shen Lim
- Respiratory Medicine, Nottingham University Hospitals NHS Trust, City Hospital Campus, Nottingham, NG5 1 PB, England, UK.
| | - Garry Meakin
- Nottingham Clinical Trials Unit, University of Nottingham, Queen's Medical Centre, Nottingham, NG7 2UH, England, UK
| | - Clare Brittain
- Nottingham Clinical Trials Unit, University of Nottingham, Queen's Medical Centre, Nottingham, NG7 2UH, England, UK
| | - Thomas Bewick
- Respiratory Medicine, Derby Teaching Hospitals NHS Foundation Trust, Uttoxeter Rd, Derby, DE22 3NE, England, UK
| | - Lelia Duley
- Nottingham Clinical Trials Unit, University of Nottingham, Queen's Medical Centre, Nottingham, NG7 2UH, England, UK
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28
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Mayo CS, Matuszak MM, Schipper MJ, Jolly S, Hayman JA, Ten Haken RK. Big Data in Designing Clinical Trials: Opportunities and Challenges. Front Oncol 2017; 7:187. [PMID: 28913177 PMCID: PMC5583160 DOI: 10.3389/fonc.2017.00187] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Accepted: 08/09/2017] [Indexed: 11/13/2022] Open
Abstract
Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.
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Affiliation(s)
- Charles S Mayo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - Martha M Matuszak
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - Shruti Jolly
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - James A Hayman
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
| | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States
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