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Lyden AK, Kalpakjian CZ, Spino C, Murphy SL, Lumeng JC, Lok AS. Development and Testing of the Protocol Quality Rating Tool (PQRT) to Evaluate Clinical Trial Protocol Document Quality. Clin Transl Sci 2025; 18:e70240. [PMID: 40293419 PMCID: PMC12036343 DOI: 10.1111/cts.70240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2025] [Revised: 03/29/2025] [Accepted: 04/08/2025] [Indexed: 04/30/2025] Open
Abstract
A high-quality protocol document is essential for the successful and efficient implementation of clinical trials, but there is no consensus on how clinical trial protocol document quality should be evaluated. We used a modified Delphi approach and cognitive interviews to develop a new protocol document quality assessment tool, the Protocol Quality Rating Tool (PQRT). We compiled a checklist of elements that should be included in a high-quality trial protocol document and asked experts to rate the importance of each element. We developed the PQRT by describing the expected content of each element and identified essential vs. additional (bonus) content to differentiate high- versus low-quality protocol documents and then organized the elements into 18 sections. We revised the PQRT based on feedback from and cognitive interviews with our protocol quality rating team. We then tested the PQRT using ten protocol documents previously approved by the Institutional Review Board. All the protocol quality raters found the tool easy to use and their scores were highly concordant for eight of ten protocol documents. We have developed and tested a simple tool to measure clinical trial protocol document quality and encourage other researchers to evaluate and validate it.
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Affiliation(s)
- Angela K. Lyden
- Michigan Institute for Clinical and Health ResearchUniversity of MichiganAnn ArborMichiganUSA
- Clinical Trials Support OfficeUniversity of MichiganAnn ArborMichiganUSA
| | - Claire Z. Kalpakjian
- Michigan Institute for Clinical and Health ResearchUniversity of MichiganAnn ArborMichiganUSA
- Department of Physical Medicine and RehabilitationUniversity of MichiganAnn ArborMichiganUSA
| | - Cathie Spino
- Michigan Institute for Clinical and Health ResearchUniversity of MichiganAnn ArborMichiganUSA
- Department of Biostatistics, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - Susan L. Murphy
- Michigan Institute for Clinical and Health ResearchUniversity of MichiganAnn ArborMichiganUSA
- Department of Physical Medicine and RehabilitationUniversity of MichiganAnn ArborMichiganUSA
| | - Julie C. Lumeng
- Michigan Institute for Clinical and Health ResearchUniversity of MichiganAnn ArborMichiganUSA
- Department of PediatricsUniversity of MichiganAnn ArborMichiganUSA
| | - Anna S. Lok
- Michigan Institute for Clinical and Health ResearchUniversity of MichiganAnn ArborMichiganUSA
- Division of Gastroenterology and Hepatology, Department of Internal MedicineUniversity of MichiganAnn ArborMichiganUSA
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Krommes K, Thorborg K, Clausen MB, Rathleff MS, Olesen JL, Kallemose T, Hölmich P. Self-management including exercise, education and activity modification compared to usual care for adolescents with Osgood-Schlatter (the SOGOOD trial): protocol of a randomized controlled superiority trial. BMC Sports Sci Med Rehabil 2024; 16:89. [PMID: 38643184 PMCID: PMC11032598 DOI: 10.1186/s13102-024-00870-0] [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: 09/28/2023] [Accepted: 03/25/2024] [Indexed: 04/22/2024]
Abstract
BACKGROUND Osgood-Schlatter is the most frequent growth-related injury affecting about 10% of physically active adolescents. It can cause long-term pain and limitations in sports and physical activity, with potential sequela well into adulthood. The management of Osgood-Schlatter is very heterogeneous. Recent systematic reviews have found low level evidence for surgical intervention and injection therapies, and an absence of studies on conservative management. Recently, a novel self-management approach with exercise, education, and activity modification, demonstrated favorable outcomes for adolescents with patellofemoral pain and Osgood-Schlatter in prospective cohort studies. AIM The aim of this trial is to assess the effectiveness of the novel self-management approach compared to usual care in improving self-reported knee-related function in sport (measured using the KOOS-child 'Sport/play' subscale) after a 5-month period. METHODS This trial is a pragmatic, assessor-blinded, randomized controlled trial with a two-group parallel arm design, including participants aged 10-16 years diagnosed with Osgood-Schlatter. Participants will receive 3 months of treatment, consisting of either usual care or the self-management approach including exercise, education, and activity modification, followed by 2 months of self-management. Primary endpoint is the KOOS-child 'Sport/play' score at 5 months. This protocol details the planned methods and procedures. DISCUSSION The novel approach has already shown promise in previous cohort studies. This trial will potentially provide much-needed level 1 evidence for the effectiveness of the self-management approach, representing a crucial step towards addressing the long-term pain and limitations associated with Osgood-Schlatter. TRIAL REGISTRATION Clinicaltrials.gov: NCT05174182. Prospectively registered December 30th 2021. Date of first recruitment: January 3rd 2022. Target sample size: 130 participants.
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Affiliation(s)
- Kasper Krommes
- Sports Orthopedic Research Center - Copenhagen (SORC-C), Department of Orthopedic Surgery, Amager-Hvidovre, Copenhagen University Hospital, Kettegaard Allé 30, Hvidovre, DK-2650, Denmark.
| | - Kristian Thorborg
- Sports Orthopedic Research Center - Copenhagen (SORC-C), Department of Orthopedic Surgery, Amager-Hvidovre, Copenhagen University Hospital, Kettegaard Allé 30, Hvidovre, DK-2650, Denmark
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark
| | - Mikkel Bek Clausen
- Department of Midwifery, Physiotherapy, Occupational Therapy and Psychomotor Therapy, Faculty of Health, University College Copenhagen, Sigurdsgade 26, DK-2200, Copenhagen N, Denmark
| | - Michael Skovdal Rathleff
- Center for General Practice at Aalborg University, Aalborg. Fyrkildevej 7, DK-9220, Aalborg, Denmark
- Department of Health Science and Technology, Aalborg University, Selma Lagerløfs Vej 249, DK-9220, Aalborg, Denmark
| | - Jens Lykkegaard Olesen
- Center for General Practice at Aalborg University, Aalborg. Fyrkildevej 7, DK-9220, Aalborg, Denmark
| | - Thomas Kallemose
- Department of Midwifery, Physiotherapy, Occupational Therapy and Psychomotor Therapy, Faculty of Health, University College Copenhagen, Sigurdsgade 26, DK-2200, Copenhagen N, Denmark
- Department of Clinical Research, Amager-Hvidovre, Copenhagen University Hospital, Kettegaard Alle 30, Hvidovre, DK-2610, Danmark
| | - Per Hölmich
- Sports Orthopedic Research Center - Copenhagen (SORC-C), Department of Orthopedic Surgery, Amager-Hvidovre, Copenhagen University Hospital, Kettegaard Allé 30, Hvidovre, DK-2650, Denmark
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark
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Stevens G, Dolley S, Mogg R, Connor JT. A template for the authoring of statistical analysis plans. Contemp Clin Trials Commun 2023; 34:101100. [PMID: 37388218 PMCID: PMC10300078 DOI: 10.1016/j.conctc.2023.101100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/06/2023] [Accepted: 03/10/2023] [Indexed: 07/01/2023] Open
Abstract
A number of principal investigators may have limited access to biostatisticians, a lack of biostatistical training, or no requirement to complete a timely statistical analysis plan (SAP). SAPs completed early will identify design or implementation weak points, improve protocols, remove the temptation for p-hacking, and enable proper peer review by stakeholders considering funding the trial. An SAP completed at the same time as the study protocol might be the only comprehensive method for at once optimizing sample size, identifying bias, and applying rigor to study design. This ordered corpus of SAP sections with detailed definitions and a variety of examples represents an omnibus of best practice methods offered by biostatistical practitioners inside and outside of industry. The article presents a protocol template for clinical research design, enabling statisticians, from beginners to advanced.
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Affiliation(s)
- Gary Stevens
- DynaStat Consulting, Inc., 119 Fairway Court, Bastrop, TX, 78602, USA
| | - Shawn Dolley
- Open Global Health, 710 12th St. South, Suite 2523, Arlington, VA, 22202, USA
| | - Robin Mogg
- Takeda Pharmaceuticals USA Inc., 95 Hayden Avenue, Lexington, MA, 02421, USA
| | - Jason T. Connor
- ConfluenceStat, 3102 NW 82nd Way, Cooper City, Florida, 33024, USA
- University of Central Florida College of Medicine, 6850 Lake Nona Blvd, Orlando, FL, 32827, USA
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What does a department need to get involved in clinical trials? Injury 2023:S0020-1383(23)00075-X. [PMID: 36725487 DOI: 10.1016/j.injury.2023.01.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/20/2022] [Accepted: 01/18/2023] [Indexed: 01/22/2023]
Abstract
Clinical trials are conducted to evaluate the usefulness of a drug, medical treatment, surgical intervention, radiological procedure, behavioral intervention, or preventive health care strategy. Clinical trials are challenging, time-consuming, and need careful planning and execution. There are certain requirements for an academic unit to be ready for conducting quality research, especially clinical trials. These include logistical concerns, infrastructure, appropriately trained human resources, conformity with ethical compliances and regulatory compliances as per the laws governing the respective geographical regions. Infrastructure requirements include research division space, robust data archival system, archival of imaging data, laboratory services, information technology division and facilities for the appropriate consenting process. Human resources such as principal investigators, data managers, clinical research assistants and biostatisticians are needed to execute the clinical trial as per the study design. Adherence to ethical and regulatory standards; during the conduct of the clinical trial are imperative. Strict compliance with prevailing governing laws in the country is a prerequisite for a department to get involved in clinical trials. The department also needs to put in place an institutional ethics committee; the composition of which is often governed by regulatory laws. The ethical aspects of the trial undergo a formal scrutiny by an Institute ethics committee that ensures quality care to the patient, and safeguards the patient's rights and privileges. The academic unit of any department forms the core for possible research and pursuit of clinical trials. A department with rich clinical experience and expertise in the filed aids in the execution of quality research. The academic department must consider grant writing and multiple center collaborative research projects in due course of time to further enhance the quality of clinical trials and research output.
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Hanlon AL, Lozano AJ, Prakash S, Bezar EB, Ambrosius WT, Brock G, Desai M, Pollock BH, Sammel MD, Spratt H, Welty LJ, Pomann G. A comprehensive survey of collaborative biostatistics units in academic health centers. Stat (Int Stat Inst) 2022; 11:e521. [PMID: 37502567 PMCID: PMC10369852 DOI: 10.1002/sta4.521] [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: 08/29/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 12/30/2022]
Abstract
The organizational structures of collaborative biostatistics units in academic health centers (AHCs) in the United States and their important contributions to research are an evolving and active area of discussion and inquiry. Collaborative biostatistics units may serve as a centralized resource to investigators across various disciplines or as shared infrastructure for investigators within a discipline (e.g., cancer), or a combination of both. The characteristics of such units vary greatly, and there has been no comprehensive review of their organizational structures described in the literature to date. This manuscript summarizes the current infrastructure of such units using responses from 129 leaders. Most leaders were over 45 years old, held doctoral degrees, and were on a 12-month appointment. Over half were tenured or on a tenure track and held primary appointments in a school of medicine. Career advancement metrics most important included being funded as co-investigator on NIH grants and being either first or second author on peer-reviewed publications. Team composition was diverse in terms of expertise and training, and funding sources were typically hybrid. These results provide a benchmark for collaboration models and evaluation and may be used by institutional administrators as they build, evaluate, or restructure current collaborative quantitative support infrastructure.
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Affiliation(s)
- Alexandra L. Hanlon
- Center for Biostatistics and Health Data Science, Department of StatisticsVirginia Polytechnic Institute and State UniversityRoanokeVirginiaUSA
| | - Alicia J. Lozano
- Center for Biostatistics and Health Data Science, Department of StatisticsVirginia Polytechnic Institute and State UniversityRoanokeVirginiaUSA
| | - Swathi Prakash
- Center for Biostatistics and Health Data Science, Department of StatisticsVirginia Polytechnic Institute and State UniversityRoanokeVirginiaUSA
| | - Emily B. Bezar
- Center for Biostatistics and Health Data Science, Department of StatisticsVirginia Polytechnic Institute and State UniversityRoanokeVirginiaUSA
| | - Walter T. Ambrosius
- Department of Biostatistics and Data Science, Division of Public Health SciencesWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Guy Brock
- Department of Biomedical InformaticsOhio State UniversityColumbusOhioUSA
| | - Manisha Desai
- Quantitative Sciences Unit, Stanford MedicineStanford UniversityStanfordCaliforniaUSA
| | - Brad H. Pollock
- Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Mary D. Sammel
- Center for Innovative Design & Analysis, Department of Biostatistics & Informatics, School of Public HealthUniversity of Colorado DenverDenverColoradoUSA
| | - Heidi Spratt
- Department of Biostatistics and Data Science, School of Public and Population HealthUniversity of Texas Medical BranchGalvestonTexasUSA
| | - Leah J. Welty
- Feinberg School of MedicineNorthwestern UniversityEvanstonIllinoisUSA
| | - Gina‐Maria Pomann
- Department of Biostatistics and BioinformaticsDuke University School of MedicineDurhamNorth CarolinaUSA
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Jeemon P, Reethu S, Ganapathi S, Lakshmi Kanth LR, Punnoose E, Abdullakutty J, Mattumal S, Joseph J, Joseph S, Venkateswaran C, Sunder P, Babu AS, Padickaparambil S, Neenumol KR, Chacko S, Shajahan S, Krishnankutty K, Devis S, Joseph R, Shemija B, John SA, Harikrishnan S. A multicentric, 2 × 2 factorial, randomised, open-label trial to evaluate the clinical effectiveness of structured physical activity training and cognitive behavioural therapy versus usual care in heart failure patients: a protocol for the PACT-HF trial. Wellcome Open Res 2022; 7:210. [PMID: 36105556 PMCID: PMC9445562 DOI: 10.12688/wellcomeopenres.18047.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/05/2022] [Indexed: 11/20/2022] Open
Abstract
Background: Heart failure (HF) is a multi-morbid chronic condition, which adversely affects the quality of life of the affected individual. Engaging the patient and their caregivers in self-care is known to reduce mortality, rehospitalisation and improve quality of life among HF patients. The PACT-HF trial will answer whether clinical benefits in terms of mortality and hospitalisation outcomes can be demonstrated by using a pragmatic design to explore the specific effects of physical activity, and cognitive behavioural therapy in HF patients in India. Methods: We will conduct a 2 × 2 factorial, randomized, open-label trial, which aims to see if rehabilitation strategies of structured physical activity training and cognitive behavioural therapy for depression and self-management reduce the risk of repeat hospitalisation and deaths in HF patients in India. Patients will be randomised to (1) physical activity + usual care (2) cognitive behaviour therapy + usual care, (3) physical activity + cognitive behaviour therapy + usual care, and (4) usual care at 1:1:1:1 ratio. Time to mortality will be the primary outcome. A composite of mortality and hospitalisation for HF will be the main secondary outcome. Additional secondary outcomes will include 'days alive and out of hospital', cumulative hospitalisation, quality of life, Minnesota Living with Heart Failure questionnaire score, depression score, six minutes walking distance, handgrip strength, and adherence to medicines and lifestyle. The effects of intervention on the primary outcome will be estimated from Cox proportional hazard models. For the continuous secondary outcome variables, differences between randomised groups will be estimated from linear mixed models or generalised estimating equations (GEE) as appropriate. Discussion: PACT-HF is designed to provide reliable evidence about the balance of benefits and risks conferred by physical activity and cognitive behavioural therapy-based cardiac rehabilitation for those with HF, irrespective of their initial disease severity.
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Affiliation(s)
- Panniyammakal Jeemon
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF) and Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, India
| | - Salim Reethu
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Sanjay Ganapathi
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Lakshmipuram Rajappan Lakshmi Kanth
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | | | | | | | | | - Stigi Joseph
- Little flower hospital and research centre, Angamali, India
| | | | | | - Abraham Samuel Babu
- Department of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India
| | - Sebastian Padickaparambil
- Department of Clinical Psychology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India
| | - Kandagathuparambil Rajan Neenumol
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Susanna Chacko
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | - Shamla Shajahan
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
| | | | - Selma Devis
- Little flower hospital and research centre, Angamali, India
| | | | | | | | - Sivadasanpillai Harikrishnan
- ICMR-Centre for Advanced Research and Excellence in Heart Failure (CARE-HF), Sree Chitra Thirunal Institute of Medical Sciences and Technology, Trivandrum, Kerala, 695011, India
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Dwivedi AK. How to write statistical analysis section in medical research. J Investig Med 2022; 70:1759-1770. [PMID: 35710142 DOI: 10.1136/jim-2022-002479] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2022] [Indexed: 12/15/2022]
Abstract
Reporting of statistical analysis is essential in any clinical and translational research study. However, medical research studies sometimes report statistical analysis that is either inappropriate or insufficient to attest to the accuracy and validity of findings and conclusions. Published works involving inaccurate statistical analyses and insufficient reporting influence the conduct of future scientific studies, including meta-analyses and medical decisions. Although the biostatistical practice has been improved over the years due to the involvement of statistical reviewers and collaborators in research studies, there remain areas of improvement for transparent reporting of the statistical analysis section in a study. Evidence-based biostatistics practice throughout the research is useful for generating reliable data and translating meaningful data to meaningful interpretation and decisions in medical research. Most existing research reporting guidelines do not provide guidance for reporting methods in the statistical analysis section that helps in evaluating the quality of findings and data interpretation. In this report, we highlight the global and critical steps to be reported in the statistical analysis of grants and research articles. We provide clarity and the importance of understanding study objective types, data generation process, effect size use, evidence-based biostatistical methods use, and development of statistical models through several thematic frameworks. We also provide published examples of adherence or non-adherence to methodological standards related to each step in the statistical analysis and their implications. We believe the suggestions provided in this report can have far-reaching implications for education and strengthening the quality of statistical reporting and biostatistical practice in medical research.
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Affiliation(s)
- Alok Kumar Dwivedi
- Department of Molecular and Translational Medicine, Division of Biostatistics and Epidemiology, Texas Tech University Health Sciences Center El Paso, El Paso, Texas, USA
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