Guidance for biostatisticians on their essential contributions to clinical and translational research protocol review

Development and Testing of the Protocol Quality Rating Tool (PQRT) to Evaluate Clinical Trial Protocol Document Quality

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.

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

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.

A template for the authoring of statistical analysis plans

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.

What does a department need to get involved in clinical trials?

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.

A comprehensive survey of collaborative biostatistics units in academic health centers

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.

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

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.

How to write statistical analysis section in medical research

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.