Dataset Information

The frequency and availability of population-specific patient reported outcome measures and minimal clinically important differences among approved drugs in Canada.

ABSTRACT:

Background

Patient reported outcome measures (PROMs) and minimal clinically important differences (MCIDs) are included in Canada's Common Drug Review (CDR) process to approve new drugs. Often, the measures report on the health-related quality of life (HRQoL), but can also describe the symptoms, efficacy and harms important to patients. They can be generic or population/condition specific, validated or not. We examined the frequency, availability and accessibility of validated, specific PROMs and MCIDs reported in the CDR reports.

Methods

We searched the Canadian Agency for Drugs and Technologies in Health (CADTH) on-line database for completed Common Drug Review, Clinical Review Reports (CDR-CRR) between November 2013 and February 2017. Two independent reviewers examined the reports and references for PROMs and MCIDs. Both reviewers separately categorized the PROMs and MICDs according to purpose, validation, availability and funding received. Discrepancies were rectified by consensus with a third investigator.

Results

One-hundred and five unique PROMs were extracted from 39 CDR-CRR, 57% with a HRQoL component. 91/105 (87%) referenced a validation study and 62/105 (59%) referenced a validation study in the study population of interest. Fifty-seven MCID references were extracted from 39 CDR-CRR. 34/57 (60%) were specific to the study population of interest, and 36% had a HRQoL component. 50% of PROM and 53% of MCID references were publicly available.

Conclusions

PROMs and MCIDs referenced in CDR-CRR show similar trends. The majority are validated, but not necessarily in the study population of interest. Continued critical examination is required to evaluate new drugs specific to the population of interest.

SUBMITTER: Soprovich A

PROVIDER: S-EPMC6322322 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The frequency and availability of population-specific patient reported outcome measures and minimal clinically important differences among approved drugs in Canada.

Soprovich Allison A Ingstrup Meghan M Eurich Dean T DT

Health and quality of life outcomes 20190107 1

<h4>Background</h4>Patient reported outcome measures (PROMs) and minimal clinically important differences (MCIDs) are included in Canada's Common Drug Review (CDR) process to approve new drugs. Often, the measures report on the health-related quality of life (HRQoL), but can also describe the symptoms, efficacy and harms important to patients. They can be generic or population/condition specific, validated or not. We examined the frequency, availability and accessibility of validated, specific P ...[more]

PMID: 30616654

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Project description:ImportancePatient-reported outcome measures (PROMs) allow clinicians and researchers to assess health-related information from a patient's perspective. These measures have been used more frequently over the last several decades, but an associated minimal clinically important difference (MCID) is needed to optimize their utility. This narrative review identified the top 100 most-cited otolaryngology-related PROM development and validation publications and assessed the presence and characteristics of the PROMs' associated MCID.ObservationsIn this narrative review, a literature search in Scopus and Web of Science was conducted on June 29, 2022, using keywords related to PROM development and validation studies in otolaryngology and reference lists. Studies that met the definition of a PROM and assessed an otolaryngologic disorder or study population were included for full-text review. After full-text review of 188 articles, the top 100 most-cited PROM development and validation publications, resulting in 106 total PROMs, were chosen for review. A total of 39 (37%) of the identified PROMs had an associated MCID. Of those reporting an MCID, 14 (35.9%) used an anchor-based method, 12 (30.8%) used a distribution-based method, 10 (25.6%) used both, and 3 (7.7%) did not specify or used neither method. Rhinology had the greatest number of PROMs with an associated MCID (16 of 24, 66%), and pediatrics had the fewest (1 of 13, 7.7%). The median number of citations of PROMs with an MCID was higher than those without an MCID.Conclusions and relevanceThe majority of the most-cited PROMs in otolaryngology lack an associated MCID. These data indicated that there are a multitude of PROMs that have been cited hundreds of times and used for decades without the ability to identify whether a particular change in score on the instrument is clinically meaningful. There is a need to determine and validate MCIDs for commonly used PROMs to aid clinical research and trial interpretation.

Project description:Client-reported outcomes measures (CROMs) have been previously validated for the evaluation of canine osteoarthritis. A published systematic review indicated that the 'Liverpool Osteoarthritis in Dogs' (LOAD) and the 'Canine Orthopedic Index' (COI) can be recommended for use in dogs with osteoarthritis; these CROMs have also been used in the context of measuring surgical outcomes of dogs with orthopaedic conditions. However, the minimal clinically-important differences (MCIDs) for these CROMs have not been investigated. Such estimates would be useful for investigators and regulators so that these CROMs can be used in clinical trials. Data from the RCVS Knowledge Canine Cruciate Registry were extracted, and baseline and 6 week follow-up data on dogs that had received surgery for cranial cruciate ligament rupture were used to make estimates of MCIDs using distribution-based and anchor-based methods. Data from 125 dogs were categorised based on the anchor question and LOAD and COI scores analysed accordingly. The four anchor-based methods provided a range of MCIDs for each CROM (1 to 8.8 for LOAD and 3.5 to 17.6 for COI). In the two different distribution-based methods, the MCIDs for LOAD ranged from 1.5 (effect size) to 2.4 (standard error of measurement) and the effect size method yielded a result of 2.2 for COI. The results showed that the value of the MCIDs depended on the method that was applied. Receiver operator characteristic curves provided areas under the curve (AUCs) greater than 0.7, which indicated that the cut-off point was acceptable; LOAD had the greater AUC at 0.867. In summary, the authors currently recommend a MCID of '4' for LOAD and '14' for COI although further work in other clinical contexts (such as osteoarthritis associated with chronic pain) is required to add confidence to these estimates. For the first time, we have provided estimates for MCIDs for these two CROMs which will facilitate sample size estimates in future clinical studies that use these CROMs as outcomes measures.

Project description:BACKGROUND:Using a real dataset, we highlighted several major methodological issues raised by the estimation of the Minimal Clinically Important Difference (MCID) of a Patient-Reported Outcomes instrument. We especially considered the management of missing data and the use of more than two times of measurement. While inappropriate missing data management and inappropriate use of multiple time points can lead to loss of precision and/or bias in MCID estimation, these issues are almost never dealt with and require cautious considerations in the context of MCID estimation. METHODS:We used the LIGALONGO study (French Randomized Controlled Trial). We estimated MCID on the SF-36 General Health score by comparing many methods (distribution or anchor-based). Different techniques for imputation of missing data were performed (simple and multiple imputations). We also consider all measurement occasions by longitudinal modeling, and the dependence of the score difference on baseline. RESULTS:Three hundred ninety-three patients were studied. With distribution-based methods, a great variability in MCID was observed (from 3 to 26 points for improvement). Only 0.2 SD and 1/3 SD distribution methods gave MCID values consistent with anchor-based methods (from 4 to 7 points for improvement). The choice of missing data imputation technique clearly had an impact on MCID estimates. Simple imputation by mean score seemed to lead to out-of-range estimate, but as missing not at random mechanism can be hypothesized, even multiple imputations techniques can have led to an slight underestimation of MCID. Using 3 measurement occasions for improvement led to an increase in precision but lowered estimates. CONCLUSION:This practical example illustrates the substantial impact of some methodological issues that are usually never dealt with for MCID estimation. Simulation studies are needed to investigate those issues. TRIAL REGISTRATION:NCT01240772 (ClinicalTrials.gov) registered on November 15, 2010.

Project description:OBJECTIVE:This article reviews and compares four commonly used approaches to assess patient responsiveness with a treatment or therapy (return to normal (RTN), minimal important difference (MID), minimal clinically important improvement (MCII), OMERACT-OARSI [Outcome Measures in Rheumatology-Osteoarthris Reseach Society International] (OO)) and demonstrates how each of the methods can be formulated in a multilevel modelling (MLM) framework. DESIGN:Cohort study. SETTING:A cohort of patients undergoing total hip and knee replacement were recruited from a single UK National Health Service hospital. POPULATION:400 patients from the Arthroplasty Pain Experience cohort study undergoing total hip (n=210) and knee (n=190) replacement who completed the Intermittent and Constant Osteoarthritis Pain questionnaire prior to surgery and then at 3, 6 and 12 months after surgery. PRIMARY OUTCOMES:The primary outcome was defined as a response to treatment following total hip or knee replacement. We compared baseline scores, change scores and proportion of individuals defined as 'responders' using traditional and MLM approaches with patient responsiveness. RESULTS:Using existing approaches, baseline and change scores are underestimated, and the variance of baseline and change scores overestimated in comparison with MLM approaches. MLM increases the proportion of individuals defined as responding in RTN, MID and OO criteria compared with existing approaches. Using MLM with the MCII criteria reduces the number of individuals identified as responders. CONCLUSION:MLM improves the estimation of the SD of baseline and change scores by explicitly incorporating measurement error into the model and avoiding regression to the mean when making individual predictions. Using refined definitions of responsiveness may lead to a reduction in misclassification when attempting to predict who does and does not respond to an intervention and clarifies the similarities between existing methods.

Project description:ObjectivesTo systematically review studies using machine learning (ML) algorithms to predict whether patients undergoing total knee or total hip arthroplasty achieve an improvement as high or higher than the minimal clinically important differences (MCID) in patient reported outcome measures (PROMs) (classification problem).MethodsStudies were eligible to be included in the review if they collected PROMs both pre- and postintervention, reported the method of MCID calculation and applied ML. ML was defined as a family of models which automatically learn from data when selecting features, identifying nonlinear relations or interactions. Predictive performance must have been assessed using common metrics. Studies were searched on MEDLINE, PubMed Central, Web of Science Core Collection, Google Scholar and Cochrane Library. Study selection and risk of bias assessment (ROB) was conducted by two independent researchers.Results517 studies were eligible for title and abstract screening. After screening title and abstract, 18 studies qualified for full-text screening. Finally, six studies were included. The most commonly applied ML algorithms were random forest and gradient boosting. Overall, eleven different ML algorithms have been applied in all papers. All studies reported at least fair predictive performance, with two reporting excellent performance. Sample size varied widely across studies, with 587 to 34,110 individuals observed. PROMs also varied widely across studies, with sixteen applied to TKA and six applied to THA. There was no single PROM utilized commonly in all studies. All studies calculated MCIDs for PROMs based on anchor-based or distribution-based methods or referred to literature which did so. Five studies reported variable importance for their models. Two studies were at high risk of bias.DiscussionNo ML model was identified to perform best at the problem stated, nor can any PROM said to be best predictable. Reporting standards must be improved to reduce risk of bias and improve comparability to other studies.

Dataset Information

The frequency and availability of population-specific patient reported outcome measures and minimal clinically important differences among approved drugs in Canada.

Background

Methods

Results

Conclusions

Publications

The frequency and availability of population-specific patient reported outcome measures and minimal clinically important differences among approved drugs in Canada.

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