[Methodological and reporting quality of randomized controlled trials on the treatment of benign prostatic hyperplasia with traditional Chinese medicine].

OBJECTIVE: To systematically evaluate the methodological quality and reporting quality of randomized controlled trials (RCT) on the treatment of BPH with traditional Chinese medicine (TCM), in order to provide some methodological reference for clinical practice and research. METHODS: We searched CNKI, VIP, Wanfang Data and PubMed for RCTs on the treatment of BPH with TCM published in China from January 2013 to November 2023. Two researchers screened the literature separately, and evaluated the methodological and reporting quality of the RCTs based on the Cochrane bias risk assessment tool and CONSORT TCM compound. RESULTS: Totally, 88 RCTs were included in this study. In terms of methodological quality, according to the Cochrane bias risk assessment tool, 27 biases in the process of randomization were identified as of low-risk and the other 61 of a certain risk. Among the allocation-related biases deviating from the established interventions, 76 were of low risk, 10 of a certain risk and 2 of high risk; among the compliance-related biases deviating from the established interventions, 76 were of low risk and 12 of a certain risk; among the biases due to missing outcome data, 86 were of low risk and 2 of a certain risk, while all the biases due to outcome measurement were of low risk; and among the biases from selective reporting, 65 were of low-risk, 2 of a certain risk and 21 of high-risk. In terms of reporting quality, according to the evaluation criteria of consort TCM compound, appropriate key words were used in 1 RCT (0.01%), the random assignment sequence method described in 27 (30.68%), the details of assignment limitation given in 5 (5.68%), assignment concealment mentioned in 3 (3.41%), the blind method and assignment concealment employed in 3 (3.41%), fall-offs recorded in 10 (11.36%), adverse events reported in 38 (43.18%), and limitations of the trials analyzed in 18 (20.45%). All the RCTs lacked complete intervention measures, subject flow chart, clinical trial registration and research schemes. CONCLUSION: At present, the methodological quality and reporting quality of RCTs on the treatment of BPH with TCM are generally low, with the main problems of incomplete experimental designs, lack of detailed description of randomized and blind methods, and insufficient TCM symptom evaluation of outcome indicators. Researchers should be cautious in adopting and applying the results reported, follow the CONSORT statement in design, registration, implement and reporting of the scheme, fully consider the clinical characteristics of TCM in the treatment of BPH, and reasonably design and report the evaluation indicators.

Determining the extent and frequency of on-site monitoring: a bayesian risk-based approach.

BACKGROUND: On-site monitoring is a crucial component of quality control in clinical trials. However, many cast doubt on its cost-effectiveness due to various issues, such as a lack of monitoring focus that could assist in prioritizing limited resources during a site visit. Consequently, an increasing number of trial sponsors are implementing a hybrid monitoring strategy that combines on-site monitoring with centralised monitoring. One of the primary objectives of centralised monitoring, as stated in the clinical trial guidelines, is to guide and adjust the extent and frequency of on-site monitoring. Quality tolerance limits (QTLs) introduced in ICH E6(R2) and thresholds proposed by TransCelerate Biopharma are two existing approaches for achieving this objective at the trial- and site-levels, respectively. The funnel plot, as another threshold-based site-level method, overcomes the limitation of TransCelerate's method by adjusting thresholds flexibly based on site sizes. Nonetheless, both methods do not transparently explain the reason for choosing the thresholds that they used or whether their choices are optimal in any certain sense. Additionally, related Bayesian monitoring methods are also lacking. METHODS: We propose a simple, transparent, and user-friendly Bayesian-based risk boundary for determining the extent and frequency of on-site monitoring both at the trial- and site-levels. We developed a four-step approach, including: 1) establishing risk levels for key risk indicators (KRIs) along with their corresponding monitoring actions and estimates; 2) calculating the optimal risk boundaries; 3) comparing the outcomes of KRIs against the optimal risk boundaries; and 4) providing recommendations based on the comparison results. Our method can be used to identify the optimal risk boundaries within an established risk level range and is applicable to continuous, discrete, and time-to-event endpoints. RESULTS: We evaluate the performance of the proposed risk boundaries via simulations that mimic various realistic clinical trial scenarios. The performance of the proposed risk boundaries is compared against the funnel plot using real clinical trial data. The results demonstrate the applicability and flexibility of the proposed method for clinical trial monitoring. Moreover, we identify key factors that affect the optimality and performance of the proposed risk boundaries, respectively. CONCLUSION: Given the aforementioned advantages of the proposed risk boundaries, we expect that they will benefit the clinical trial community at large, in particular in the realm of risk-based monitoring.

Radiotherapy Plan Quality Assurance in NRG Oncology Trials for Brain and Head/Neck Cancers: An AI-Enhanced Knowledge-Based Approach.

The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.

Quality Assurance in Radiotherapy (RT)-Specific Trials: Indian Scenario.

AIMS: There is evidence that proper radiotherapy trial quality assurance (RTTQA) translates into improved outcomes for patients. However, the practice of RTTQA is heterogeneous and implemented in a diverse manner across trials. In this paper, we review the RTTQA report for randomised trials (RCT) conducted in India and present our experience with RTTQA for various clinical trials and highlight the key achievements and challenges. MATERIALS AND METHODS: Search was performed using the keywords and the variations thereof for "radiotherapy" and author affiliations from India, its states and major metropolitan cities. Pubmed search filters were used to restrict results to RCT published in the past 5 years (2019-2024). Reporting of RTTQA procedures from publications and protocols was documented along with the protocol-specified dosimetric goals. We also evaluated a few clinical trials performed in the Department of Radiation Oncology at Tata Medical Center. The different RTTQA procedures and results for four representative clinical trials have been described. RESULTS: A formal RTTQA process was reported by only one out of 24 randomised controlled trials and formal dosimetric goals were pre-specified by 9 of 13 trials where IMRT was used as treatment. RTTQA requirements were tailored for each clinical trial at Tata Medical Center. For the HYPORT trial, the RTTQA process focused on ensuring the matchline doses were homogenous. HYPORT B trial commissioned the use of a simultaneous integrated boost technique which emphasised conformal avoidance of dose spillage to contralateral breast and lung. HYPORT Adjuvant and PROPARA trials are multicentre clinical trials. While HYPORT Adjuvant focussed on ensuring that the dose delivery met the predefined constraints, segmentation of the target volume was important for the PROPARA trial. CONCLUSION: We demonstrate different RTTQA procedures required for representative clinical trials and highlight key challenges encountered.

Does Central Statistical Monitoring Improve Data Quality? An Analysis of 1,111 Sites in 159 Clinical Trials.

BACKGROUND: Central monitoring aims at improving the quality of clinical research by pro-actively identifying risks and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. This paper, focusing on statistical data monitoring (SDM), is the second of a series that attempts to quantify the impact of central monitoring in clinical trials. MATERIAL AND METHODS: Quality improvement was assessed in studies using SDM from a single large central monitoring platform. The analysis focused on a total of 1111 sites that were identified as at-risk by the SDM tests and for which the study teams conducted a follow-up investigation. These sites were taken from 159 studies conducted by 23 different clinical development organizations (including both sponsor companies and contract research organizations). Two quality improvement metrics were assessed for each selected site, one based on a site data inconsistency score (DIS, overall -log10 P-value of the site compared with all other sites) and the other based on the observed metric value associated with each risk signal. RESULTS: The SDM quality metrics showed improvement in 83% (95% CI, 80-85%) of the sites across therapeutic areas and study phases (primarily phases 2 and 3). In contrast, only 56% (95% CI, 41-70%) of sites showed improvement in 2 historical studies that did not use SDM during study conduct. CONCLUSION: The results of this analysis provide clear quantitative evidence supporting the hypothesis that the use of SDM in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

Consensus on the definition and assessment of external validity of randomized controlled trials: A Delphi study.

External validity is an important parameter that needs to be considered for decision making in health research, but no widely accepted measurement tool for the assessment of external validity of randomized controlled trials (RCTs) exists. One of the most limiting factors for creating such a tool is probably the substantial heterogeneity and lack of consensus in this field. The objective of this study was to reach consensus on a definition of external validity and on criteria to assess the external validity of RCTs included in systematic reviews. A three-round online Delphi study was conducted. The development of the Delphi survey was based on findings from a previous systematic review. Potential panelists were identified through a comprehensive web search. Consensus was reached when at least 67% of the panelists agreed to a proposal. Eighty-four panelists from different countries and various disciplines participated in at least one round of this study. Consensus was reached on the definition of external validity ("External validity is the extent to which results of trials provide an acceptable basis for generalization to other circumstances such as variations in populations, settings, interventions, outcomes, or other relevant contextual factors"), and on 14 criteria to assess the external validity of RCTs in systematic reviews. The results of this Delphi study provide a consensus-based reference standard for future tool development. Future research should focus on adapting, pilot testing, and validating these criteria to develop measurement tools for the assessment of external validity.

Pilot trials may improve the quality of full-scale trials: a meta-research study.

OBJECTIVES: Evidence on the value of pilot trials for subsequent trial's quality is scarce. This study aims to determine if a pilot trial improves the quality of the full-scale trial. STUDY DESIGN AND SETTING: We searched PubMed for pilot trials and their subsequent full-scale trials. The meta-analysis of the full-scale trials was used to identify other full-scale trials on the same research topic but without a pilot trial. Markers of trial quality included publication outcomes and Cochrane Risk of Bias (RoB) assessment. RESULTS: Fifty-eight full-scale trials with a pilot trial and 151 full-scale trials without were identified from 47 meta-analyses. Trials with a pilot trial were published 0.9 years sooner (mean ± standard deviation: 1.7 ± 1.0 vs. 2.6 ± 2.0, P = 0.005) and in peer-reviewed journals with higher impact factors (60.9 ± 75.0 vs. 24.8 ± 50.3, P < 0.001). A pilot trial's presence was associated with lower risk of bias in full-scale trial random sequence generation (OR [95% CI]: 4.05 [1.27-12.91]), allocation concealment (2.89 [1.07-7.83]), and participants/researchers masking (4.31 [1.37-13.50]), but not outcome assessment masking (1.03 [0.49-2.18]), incomplete outcome data (1.27 [0.47-3.42]), and selective reporting (1.23 [0.44-3.46]). CONCLUSION: Conducting a pilot trial may enhance the quality of the subsequent full-scale trial.

Implementation of Machine Learning Models to Ensure Radiotherapy Quality for Multicenter Clinical Trials: Report from a Phase III Lung Cancer Study.

The outcome of the patient and the success of clinical trials involving RT is dependent on the quality assurance of the RT plans. Knowledge-based Planning (KBP) models using data from a library of high-quality plans have been utilized in radiotherapy to guide treatment. In this study, we report on the use of these machine learning tools to guide the quality assurance of multicenter clinical trial plans. The data from 130 patients submitted to RTOG1308 were included in this study. Fifty patient cases were used to train separate photon and proton models on a commercially available platform based on principal component analysis. Models evaluated 80 patient cases. Statistical comparisons were made between the KBP plans and the original plans submitted for quality evaluation. Both photon and proton KBP plans demonstrate a statistically significant improvement of quality in terms of organ-at-risk (OAR) sparing. Proton KBP plans, a relatively emerging technique, show more improvements compared with photon plans. The KBP proton model is a useful tool for creating proton plans that adhere to protocol requirements. The KBP tool was also shown to be a useful tool for evaluating the quality of RT plans in the multicenter clinical trial setting.

Risk-Based Monitoring in Clinical Trials: 2021 Update.

Clinical trial quality depends on ensuring participant safety and data integrity, which require careful management throughout the trial lifecycle, from protocol development to final data analysis and submission. Recent developments-including new regulatory requirements, emerging technologies, and trial decentralization-have increased adoption of risk-based monitoring (RBM) and its parent framework, risk-based quality management (RBQM) in clinical trials. The Association of Clinical Research Organizations (ACRO), recognizing the growing importance of these approaches, initiated an ongoing RBM/RBQM landscape survey project in 2019 to track adoption of the eight functional components of RBQM. Here we present results from the third annual survey, which included data from 4889 clinical trials ongoing in 2021. At least one RBQM component was implemented in 88% of trials in the 2021 survey, compared with 77% in 2020 and 53% in 2019. The most frequently implemented components in 2021 were initial and ongoing risk assessments (80 and 78% of trials, respectively). Only 7% of RBQM trials were Phase IV, while the proportions of Phase I-III trials ranged 27-36%. Small trials (< 300 participants) accounted for 60% of those implementing RBQM. The therapeutic areas with the largest number of RBQM trials were oncology (38%), neurology (10%), and infectious diseases (9%). The 2021 survey confirmed a pattern of increasing RBM/RBQM adoption seen in earlier surveys, with risk assessments, which have broad regulatory support, driving RBQM growth; however, one area requiring further development is implementation of centralized monitoring combined with reductions in source data verification (SDV) and source data review (SDR).

Evaluating the evaluators - Developing evidence of quality oversight effectiveness for clinical trial monitoring: Source data verification, source data review, statistical monitoring, key risk indicators, and direct measure of high risk errors.

BACKGROUND: Detailed information about clinical trial quality typically is not published in primary publications. This is a significant issue for physicians, advisory groups, and regulators. In addition, the efficacy of methods to find critical errors that affect trial integrity has not been tested. For more than 20 years, visits to research sites for source data verification (SDV) have been the gold standard method for oversight by pharmaceutical, biotech, device, and vaccine manufacturers. However, there is no evidence of its effectiveness and significant evidence of its lack of effectiveness. GAPS: We consulted documents from the Food and Drug Administration (FDA), European Medicines Association (EMA), and International Council for Harmonization (ICH) to break down components of this pivotal issue into gaps in monitoring, oversight cost, and test validation and effectiveness. RECOMMENDATIONS: We recommend that the pharma, biotech, academic, and publishing communities develop and provide reference datasets with defined errors for trials similar to the reference standards for analytic tests; systematically test the different monitoring methods using the reference datasets as well as provide sensitivity, specificity, positive and negative predictive values, and time to critical finding for each methodology for different types of trial errors; and publish the details of trial quality in each publication, including the number of major deviations. CONCLUSIONS: This will allow the scientific community to improve measurements of research quality, evaluate new methods, and compare the effectiveness of different oversight approaches in the same environment.

Quality of Life After Deep Brain Stimulation of Pediatric Patients with Dyskinetic Cerebral Palsy: A Prospective, Single-Arm, Multicenter Study with a Subsequent Randomized Double-Blind Crossover (STIM-CP).

BACKGROUND: Patients with dyskinetic cerebral palsy are often severely impaired with limited treatment options. The effects of deep brain stimulation (DBS) are less pronounced than those in inherited dystonia but can be associated with favorable quality of life outcomes even in patients without changes in dystonia severity. OBJECTIVE: The aim is to assess DBS effects in pediatric patients with pharmacorefractory dyskinetic cerebral palsy with focus on quality of life. METHODS: The method used is a prospective, single-arm, multicenter study. The primary endpoint is improvement in quality of life (CPCHILD [Caregiver Priorities & Child Health Index of Life with Disabilities]) from baseline to 12 months under therapeutic stimulation. The main key secondary outcomes are changes in Burke-Fahn-Marsden Dystonia Rating Scale, Dyskinesia Impairment Scale, Gross Motor Function Measure-66, Canadian Occupational Performance Measure (COPM), and Short-Form (SF)-36. After 12 months, patients were randomly assigned to a blinded crossover to receive active or sham stimulation for 24 hours each. Severity of dystonia and chorea were blindly rated. Safety was assessed throughout. The trial was registered at ClinicalTrials.gov, number NCT02097693. RESULTS: Sixteen patients (age: 13.4 ± 2.9 years) were recruited by seven clinical sites. Primary outcome at 12-month follow-up is as follows: mean CPCHILD increased by 4.2 ± 10.4 points (95% CI [confidence interval] -1.3 to 9.7; P = 0.125); among secondary outcomes: improvement in COPM performance measure of 1.1 ± 1.5 points (95% CI 0.2 to 1.9; P = 0.02) and in the SF-36 physical health component by 5.1 ± 6.2 points (95% CI 0.7 to 9.6; P = 0.028). Otherwise, there are no significant changes. CONCLUSION: Evidence to recommend DBS as routine treatment to improve quality of life in pediatric patients with dyskinetic cerebral palsy is not yet sufficient. Extended follow-up in larger cohorts will determine the impact of DBS further to guide treatment decisions in these often severely disabled patients. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Can quality management drive evidence generation?

Recent guidance documents from international regulators emphasize the importance of thoughtful trial design and risk-based oversight in delivering reliable results. In practice, these recommendations are often implemented in a fragmented manner, reducing their effectiveness. We argue that collaborative, cross-stakeholder engagement that prioritizes both optimal trial design and tailored oversight are a necessary and effective approach to modernize quality management. This practice is at the core of Quality by Design, an approach that involves identifying important errors that could undermine trial credibility or participant safety and addressing them proactively. While Quality by Design is well suited for clinical trials supporting regulatory approval of a new medicinal product, we describe how the approach is equally relevant for pragmatic trials, including those conducted in the context of a pandemic.

Development and implementation of standardized study performance metrics for a VA healthcare system clinical research consortium.

The cost of conducting clinical trials is continuously increasing and is driven in large part by the time and resources required to activate trials and reach accrual targets. The impact of low enrollment in a clinical trial can negatively affect the validity of study results and delay its generalizability to the broader population. Quality is a multidimensional concept which could relate to the design, conduct, and analysis of a trial, its clinical relevance, protection/safety of study participants, or quality of reporting. Furthermore, the quality of controlled trials is of obvious relevance to systematic reviews and if the "raw material" or "data" is flawed then the conclusions of systematic reviews cannot be trusted. To date, the literature surrounding the establishment of standardized study enrollment and quality metrics to assess site performance in clinical trial consortiums is scarce. The lack of these metrics presents challenges to study site teams, sponsors, and other clinical research enterprise key stakeholders for adequately monitoring and evaluating study site performance as it relates to fulfilling trial enrollment and quality goals. The Department of Veterans Affairs (VA) Cooperative Studies Program (CSP) Network of Dedicated Enrollment Sites (NODES) undertook an effort to determine the feasibility of establishing and implementing standardized study enrollment and quality metrics for a clinical research consortium (NODES) as a tool to evaluate its performance. In this manuscript, we describe the development and implementation of standardized study enrollment and quality metrics to assess site performance across studies in our clinical research consortium.

[The development and main achievements of clinical trials for anti-cancer investigational new drug in the past 60 years in China (1960-2020)].

Medical oncology is a subject characterized by drug therapy. Continuous research and development (R&D) of high-efficiency and low-toxic anti-cancer drugs is the premise of the development of medical oncology. Clinical trials play an indispensable role in the process from drug R&D to application, which determines the success or failure of a new drug. The clinical trials for anti-cancer investigational new drug (IND) in China began in 1960, and have developed rapidly since 2008. With the guidance and support of national policies, as well as involved by all aspects of the society, the R&D of anti-cancer drugs in China has changed from imitation to innovation. China innovative anti-cancer drugs have been widely recognized in the world, and more and more new domestic anti-cancer drugs have been used in clinical practice, bringing benefit to Chinese cancer patients. This article reviews the development of the clinical trials for anti-cancer IND in China from 1960 to 2020, and the main achievements having been made in the past 60 years. A thorough understanding of this history will help us keep in mind the mission and grasp the direction, as to make more achievements when implementing the strategy of "Healthy China" .

Central monitoring in a randomized, open-label, controlled phase 3 clinical trial for a treatment-shortening regimen for pulmonary tuberculosis.

INTRODUCTION: With the growing use of online study management systems and rapid availability of data, timely data review and quality assessments are necessary to ensure proper clinical trial implementation. In this report we describe central monitoring used to ensure protocol compliance and accurate data reporting, implemented during a large phase 3 clinical trial. MATERIAL AND METHODS: The Tuberculosis Trials Consortium (TBTC) Study 31/AIDS Clinical Trials Group (ACTG) study A5349 (S31) is an international, multi-site, randomized, open-label, controlled, non-inferiority phase 3 clinical trial comparing two 4-month regimens to a standard 6 month regimen for treatment of drug-susceptible tuberculosis (TB) among adolescents and adults with a sample size of 2500 participants. RESULTS: Central monitoring utilized primary study data in a five-tiered approach, including (1) real-time data checks & topic-specific intervention reports, (2) missing forms reports, (3) quality assurance metrics, (4) critical data reports and (5) protocol deviation identification, aimed to detect and resolve quality challenges. Over the course of the study, 240 data checks and reports were programed across the five tiers used. DISCUSSION: This use of primary study data to identify issues rapidly allowed the study sponsor to focus quality assurance and data cleaning activities on prioritized data, related to protocol compliance and accurate reporting of study results. Our approach enabled us to become more efficient and effective as we informed sites about deviations, resolved missing or inconsistent data, provided targeted guidance, and gained a deeper understanding of challenges experienced at clinical trial sites. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (Identifier: NCT02410772) on April 8, 2015.

Factors influencing the quality of clinical trials on traditional Chinese medicine-Qualitative interviews with trial auditors, clinicians and academic researchers.

BACKGROUND: As clinical trials evaluating the efficacy of traditional Chinese medicine (TCM) therapies have increased, several empirical studies have shown that the quality of TCM trials is generally low in terms of risk of bias. This qualitative study aimed to investigate the factors influencing the quality of TCM clinical trials to provide strategic advice on trial quality improvement. METHODS: One focus group with clinical trial auditors (n = 4) and six in-depth semi-structured interviews with clinical research organization managers (n = 2), lecturers and researchers in TCM academic institutions (n = 2), a chief physician in a TCM oncology department and a PhD candidate specialized in non-pharmaceutical TCM interventions were conducted. The interviews were audio-recorded, transcribed verbatim and thematically analyzed. RESULTS: Factors that influenced the quality of TCM clinical trials emerged with the following 6 themes: trial design; trialists/participants; trial conducting; TCM specified problems; trial monitoring, and finally societal influences. The lack of expertise and time inputs of the trialists were repeatedly mentioned. Methodological difficulties experienced when conducting TCM trials including calculating sample size, analyzing the efficacy of TCM decoctions with multiple ingredients, blinding in trials investigating non-pharmaceutical TCM interventions were highlighted. Interviewees agreed that third-party monitoring can help improving trial quality and improve participant welfare, may accelerate recruiting processes and increase compliance; however more comprehensive regulations and funding requirements would be needed. CONCLUSIONS: This study identified real-life issues influencing the quality of TCM clinical trials from design to reporting. In addition to mandatory training for TCM trial designers and coordinators, more effective institutional oversight is required. Future studies should explore specific measures to address the methodological problems in TCM trials and explore how the quality of TCM trials can affect further evidence synthesis and clinical practice.

Randomized controlled trials comparing surgery to non-operative management in neurosurgery: a systematic review.

BACKGROUND: A randomized controlled trial (RCT) remains the pinnacle of clinical research design. However, RCTs in neurosurgery, especially those comparing surgery to non-operative treatment, are rare and their relevance and applicability have been questioned. This study set out to assess trial design and quality and identify their influence on outcomes in recent neurosurgical trials that compare surgery to non-operative treatment. METHODS: From 2000 to 2017, PubMed and Embase databases and four trial registries were searched. RCTs were evaluated for study design, funding, adjustments to reported outcome measures, accrual of patients, and academic impact. RESULTS: Eighty-two neurosurgical RCTs were identified, 40 in spine disorders, 19 neurovascular and neurotrauma, 11 functional neurosurgery, ten peripheral nerve, and two pituitary surgery. Eighty-four RCTs were registered, of which some are ongoing. Trial registration rate differed per subspecialty. Funding was mostly from non-industry institutions (58.5%), but 25.6% of RCTs did not report funding sources. 36.4% of RCTs did not report a difference between surgical and non-operative treatment, 3.7% favored non-operative management. Primary and secondary outcome measures were changed in 13.2% and 34.2% of RCTs respectively and varied by subspecialty. 41.9% of RCTs subtracted ≥ 10% of the anticipated accrual and 12.9% of RCTs added ≥ 10%. 7.3% of registered RCTs were terminated, mostly due to too slow recruitment. Subspecialty, registration, funding, masking, population size, and changing outcome measures were not significantly associated with a reported benefit of surgery. High Jadad scores (≥ 4) were negatively associated with a demonstration of surgical benefit (P < 0.05). CONCLUSIONS: Neurosurgical RCTs comparing surgical to non-operative treatment often find a benefit for surgical treatment. Changes to outcome measurements and anticipated accrual are common and funding sources are not always reported.

Investigation of the Study Characteristics Affecting Clinical Trial Quality Using the Protocol Deviations Leading to Exclusion of Subjects From the Per Protocol Set Data in Studies for New Drug Application: A Retrospective Analysis.

BACKGROUND: The concept of the risk-based approach has been introduced as an effort to secure the quality of clinical trials. In the risk-based approach, identification and evaluation of risk in advance are considered important. For recently completed clinical trials, we investigated the relationship between study characteristics and protocol deviations leading to the exclusion of subjects from Per Protocol Set (PPS) efficacy analysis. METHODS: New drugs approved in Japan in the fiscal year 2014-2015 were targeted in the research. The reasons for excluding subjects from the PPS efficacy analysis were described in 102 trials out of 492 in the summary of new drug application documents, which was publicly disclosed after the drug's regulatory approval. The author extracted these reasons along with the numbers of the cases and the study characteristics of each clinical trial. Then, the direct comparison, univariate regression analysis, and multivariate regression analysis was carried out based on the exclusion rate. RESULT: The study characteristics for which exclusion of subjects from the PPS efficacy analysis were frequently observed was multiregional clinical trials in study region; inhalant and external use in administration route; Anti-infective for systemic use; Respiratory system, Dermatologicals, and Nervous system in therapeutic drug under the Anatomical Therapeutic Chemical Classification. In the multivariate regression analysis, the clinical trial variables of inhalant, Respiratory system, or Dermatologicals were selected as study characteristics leading to a higher exclusion rate. CONCLUSIONS: The characteristics of the clinical trial that is likely to cause protocol deviations that will affect efficacy analysis were suggested. These studies should be considered for specific attention and priority observation in the trial protocol or its monitoring plan and execution, such as a clear description of inclusion/exclusion criteria in the protocol, development of training materials to site staff, and/or trial subjects as specific risk-alleviating measures.

A Quantitative Assessment of the Reporting Quality of Herbal Medicine Research: The Road to Improvement.

OBJECTIVES: To quantify different aspects of the quality of reporting of herbal medicine clinical trials, to determine how that quality is affecting the conclusions of meta-analyses, and to target areas for improvement in future herbal medicine research reporting. STUDY DESIGN: The Electronic databases PubMed, Academic Search Premier, ScienceDirect, and Alt HealthWatch were searched for meta-analyses of herbal medicines in refereed journals and Cochrane Reviews in the years 2000-2004 and 2010-2014. The search was limited to meta-analyses of randomized controlled trials involving humans and published in English. Judgments and descriptions within the meta-analyses were used to report on risks of bias in the included clinical trials and the meta-analyses themselves. RESULTS: Out of 3264 citations, 9 journal-published meta-analyses were selected from 2000 to 2004, 116 from 2010 to 2014, and 44 Cochrane Reviews from 2010 to 2014. Across both time frames and categories of publication, <42% of the trials included in the meta-analyses described adequate randomization; <19% described concealment methods; <26% described double blinding; <29% described outcome assessment blinding, ≤53% discussed incomplete data, and <36% were nonselective in their reporting. Less than 54% of trials reported on adverse events and 64% of meta-analyses did not include a single trial with a low risk of bias. Taxonomic verification and chemical characterization of test products were infrequent in trials. Only 40% of meta-analyses considered publication bias and, of those that did, 90% found evidence for it. Cochrane Reviews were more likely than other sources to make negative conclusions of efficacy or to defer conclusions because of the absence of high quality trials. CONCLUSIONS: Meta-analyses of herbal medicines include a significant number of clinical trials that do not meet the recommended standards for clinical trial reporting. This quantitative assessment identified significant publication bias and other bias risks that may be due to inadequate trial design or incomplete reporting of outcomes. Suggested improvements to herbal medicine clinical trial reporting are discussed.

Myotonic Dystrophy Health Index: initial evaluation of a disease-specific outcome measure.

INTRODUCTION: In preparation for clinical trials we examine the validity, reliability, and patient understanding of the Myotonic Dystrophy Health Index (MDHI). METHODS: Initially we partnered with 278 myotonic dystrophy type-1 (DM1) patients and identified the most relevant questions for the MDHI. Next, we used factor analysis, patient interviews, and test-retest reliability assessments to refine and evaluate the instrument. Lastly, we determined the capability of the MDHI to differentiate between known groups of DM1 participants. RESULTS: Questions in the final MDHI represent 17 areas of DM1 health. The internal consistency was acceptable in all subscales. The MDHI had a high test-retest reliability (ICC = 0.95) and differentiated between DM1 patient groups with different disease severities. CONCLUSIONS: Initial evaluation of the MDHI provides evidence that it is valid and reliable as an outcome measure for assessing patient-reported health. These results suggest that important aspects of DM1 health may be measured effectively using the MDHI.