GetReal: from efficacy in clinical trials to relative effectiveness in the real world

Multicenter observational study on the efficacy of selective Janus Kinase-1 inhibitor upatacitinib in rheumatoid arthritis

BACKGROUND

Upadacitinib (UPA) is a selective, reversible Janus kinase inhibitor (JAKi) approved for the treatment of RA. However, there is still no solid evidence on the long-term efficacy of UPA in treated patients. The purpose of this study was to determine the efficacy of UPA to obtain remission or low disease activity (LDA) in a series of UPA patients in patients with RA after 6 and 12 months of treatment in a real-world setting.

METHODS

A series of 111 consecutive patients treated with UPA in 23 rheumatology centers were enrolled. Personal history, treatment history and disease activity at baseline, after 6 and 12 months were recorded. Intention-to-treat (ITT) and per-protocol (PP) analyses assessed achievement of remission or LDA or defined as DAS28 <2.6 and ≤3.2, respectively. Logistic regression analysis examined the role of several independent factors on the reduction of disease activity after 6 months of treatment.

RESULTS

Of the initial group of 111 subjects at baseline, 86 and 29 participants completed clinical assessments at 6 and 12 months. According to ITT analysis, the rates of remission and LDA were 18% and 18% at 6 months and 31.5% and 12.5% at 12 months, respectively. PP analysis showed higher rates of remission and LDA at 6 (23.3% and 19.8%) and 12 months (55.2% and 20.7%). Results of multivariate logistic regression analysis indicated that a low DAS28 score (P=0.045) was the only predictor of achieving remission at 6 months. None of the baseline factors predicted remission/LDA at 6 months.

CONCLUSIONS

RA patients treated with UPA achieved a significant rate of disease remission or LDA in a real-world setting. The 6-month response was found to depend only on the baseline value of DAS28, while it was not influenced by other factors such as disease duration, line of treatment or concomitant therapy with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) or corticosteroids.

Analysis of survival rate and persistence predictors of baricitinib in real-world data from a large cohort of rheumatoid arthritis patients

Objectives

The persistence in therapy of rheumatoid arthritis drugs and particularly bDMARD is a limiting factor for their long-term use. The randomized controlled trials (RCTs) may not reflect real-world contexts due to strict inclusion and exclusion criteria. Baricitinib, which targets both JAK1 and JAK2, has been used in Italy for several years. The aim of this multi-center study is to assess the real world persistence on therapy of baricitinib in RA patients and to identify predictive factors of baricitinib's survival rate.

Methods

This is a retrospective, multicentric, Italian, longitudinal study. All patients were enrolled according to the following criteria: a) age ≥ 18 years old; b) diagnosed with RA according 2010 ACR/EULAR classification criteria; c) treated with baricitinib. In order to describe baricitinib clinical efficacy, the survival rate was evaluated by The Kaplan-Meier curve. Then, predictive factors of drug retention rate were assessed by performing the Cox analysis, identifying which risk factors influenced treatment persistence.

Results

Overall, we included 478 patients treated with baricitinib. Among them, 380 (79.5%) were females. Baricitinib's survival rate was 94.6% at 6 months, 87.9% at 12 months, 81.7% at 24 months and 53.4% at 48 months. The Cox analysis regression showed that a higher bDMARDs/tsDMARD line of therapy seems to be a negative prognostic factor for the drug retention rate (HR 1.26 CI 95% 1.07-1.49, p = 0.006.

Conclusion

Real-life study confirms baricitinib effectiveness up to 4 years, but previous treatment with bDMARDs was a negative prognostic factor for its survival rate.

Novel hormonal therapy versus standard of care-A registry-based comparative effectiveness evaluation for mCRPC-patients

BACKGROUND

This paper presents results from one of the few comparative effectiveness evaluations of novel antiandrogen medications (NHT) against standard of care (SoC) for patients suffering from metastatic castrate-resistant prostate cancer (mCRPC).

METHODS

The design and the analysis are published in a protocol before accessing outcome data. Two groups of patients are balanced on hundreds of important covariates measured before the prostate cancer diagnosis and up to the date of the prescription. While the design yields balance on the observed covariates, one cannot discard the possibility that unobserved confounders are not balanced. The unconfoundedness assumption is assessed by estimating placebo regressions on two health measures, not included in the design but added together with the outcome data after protocol publication.

RESULTS

We find a substantial (64 percent) increase in mortality for patients prescribed with NHT rather than SoC. However, based on the results from one of the two placebo regressions, we cannot rule out that the difference in mortality may be due to confounding. Using a bounding strategy of the effect, we can, however, rule out that NHT reduces mortality compared to SoC. Under an empirical valid assumption that most mCRPC patients who die suffer from bone metastases, we have a strong indication of increased skeleton-related events in patients if prescribed NHT against SoC.

CONCLUSIONS

Generally, the SoC for this group of patients is docetaxel. Given the substantially higher costs of many of the NHT, the finding of no positive effects from NHT on both mortality and SRE is important. More comparative studies, including studies analysing quality of life outcomes, are thus needed.

The potential impact of policies and structural interventions in reducing cardiovascular disease and mortality: a systematic review of simulation-based studies

Background

The aim of the study was to investigate the potential effect of different structural interventions for preventing cardiovascular disease.

Methods

Medline and EMBASE were searched for peer-reviewed simulation-based studies of structural interventions for prevention of cardiovascular disease. We performed a systematic narrative synthesis.

Results

A total of 54 studies met the inclusion criteria. Diet, nutrition, tobacco and alcohol control and other programmes are among the policy simulation models explored. Food tax and subsidies, healthy food and lifestyles policies, palm oil tax, processed meat tax, reduction in ultra-processed foods, supplementary nutrition assistance programmes, stricter food policy and subsidised community-supported agriculture were among the diet and nutrition initiatives. Initiatives to reduce tobacco and alcohol use included a smoking ban, a national tobacco control initiative and a tax on alcohol. Others included the NHS Health Check, WHO 25 × 25 and air quality management policy.

Future work and limitations

There is significant heterogeneity in simulation models, making comparisons of output data impossible. While policy interventions typically include a variety of strategies, none of the models considered possible interrelationships between multiple policies or potential interactions. Research that investigates dose-response interactions between numerous modifications as well as longer-term clinical outcomes can help us better understand the potential impact of policy-level interventions.

Conclusions

The reviewed studies underscore the potential of structural interventions in addressing cardiovascular diseases. Notably, interventions in areas such as diet, tobacco, and alcohol control demonstrate a prospective decrease in cardiovascular incidents. However, to realize the full potential of such interventions, there is a pressing need for models that consider the interplay and cumulative impacts of multiple policies. Rigorous research into holistic and interconnected interventions will pave the way for more effective policy strategies in the future.

Study registration

The study is registered as PROSPERO CRD42019154836.

Funding

This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 17/148/05.

Causal inferences and real-world evidence: A comparative effectiveness evaluation of abiraterone acetate against enzalutamide

Regulatory authorities are recognizing the need for real-world evidence (RWE) as a complement to randomized controlled trials in the approval of drugs. However, RWE needs to be fit for regulatory purposes. There is an ongoing discussion regarding whether pre-publication of a protocol on appropriate repositories, e.g. ClinicalTrials.gov, would increase the quality of RWE or not. This paper illustrates that an observational study based on a pre-published protocol can entail the same level of detail as a protocol for a randomized experiment. The strategy is exemplified by designing a comparative effectiveness evaluation of abiraterone acetate against enzalutamide in clinical practice. These two cancer drugs are prescribed to patients with advanced prostate cancer. Two complementary designs, including pre-analysis plans, were published before data on outcomes and proxy-outcomes were obtained. The underlying assumptions are assessed and both analyses show an increased mortality risk from being prescribed abiraterone acetate compared to enzalutamide.

Survival Benefit of Adjuvant Chemotherapy in Node-Positive Breast Cancer With a 21-Gene Recurrence Score of 14 to 25: A Real-World Study Based on the Inverse Probability of Treatment Weighting Method

INTRODUCTION

The role of recurrence score in predicting the benefits of adjuvant chemotherapy for lymph-node-positive breast cancer remains uncertain. We studied chemotherapy usage in patients with 1 to 3 positive lymph nodes and a recurrence score (RS) of 25 or lower to assess changes in clinical practice based on the RxPONDER trial.

METHODS

A retrospective study using the SEER database identified female patients diagnosed with ER-positive, HER2-negative breast cancer, 1 to 3 positive lymph nodes, and an RS of 25 or lower between 2010 and 2015. Patients were divided into nonchemotherapy and chemotherapy groups, with propensity score weighting to balance clinicopathologic factors.

RESULTS

Among 7965 patients, 5774 (72.5%) were in the nonchemotherapy group, while 2191 (27.5%) were in the chemotherapy group. Median follow-up was 39 months. Breast cancer accounted for 67 deaths, while 128 deaths were due to other causes. The weighted 5-year overall survival (OS) rates were 95.7% for the nonchemotherapy group and 97.2% for the chemotherapy group. For high-risk patients, the weighted 5-year OS rates were 95.2% and 97.0% for the nonchemotherapy and chemotherapy groups, respectively, with a significant absolute difference of 1.8% (P = .014). Multivariate analysis showed a significant difference in weighted hazard ratios for OS between the nonchemotherapy and chemotherapy groups in high-risk patients (hazard ratio: 0.64; 95% CI: 0.48-0.86). However, there were no significant differences in weighted hazard ratios for lower-risk patients, and similar results were observed for breast cancer-specific survival (BCSS).

CONCLUSION

Patients with ER-positive, HER2-negative breast cancer and 1 to 3 positive lymph nodes, assessed by a 21-gene RS of 0 to 25, exhibited heterogeneous prognosis. Adjuvant chemotherapy provided a significant survival benefit, especially for patients with RS of 14 to 25, particularly those with invasive ductal carcinoma (IDC) and 2 to 3 positive lymph nodes.

Clinico-Genomic Characterization of Patients with Metastatic Urothelial Carcinoma in Real-World Practice Identifies a Novel Bladder Immune Performance Index (BIPI)

PURPOSE

This retrospective analysis of the largest available clinico-genomic database used de-identified patient-level electronic health record-derived real-world data (RWD) combined with FoundationOne® comprehensive genomic profiling (CGP) to characterize patients with metastatic urothelial carcinoma (mUC) treated in the real-world setting, detect potential biomarkers, and develop a bladder immune performance index (BIPI).

EXPERIMENTAL DESIGN

Patients with mUC who started front-line single-agent immune checkpoint inhibitors (ICIs) and an unmatched group treated with front-line platinum-based chemotherapy between January 1, 2011 and September 30, 2019 were selected. Clinical and genomic data were correlated with overall survival (OS). A novel BIPI predicting outcome with ICIs was developed using machine learning methods and validated using data from a phase II trial (NCT02951767).

RESULTS

In ICI-treated patients (n=118), high tumor mutational burden (≥10 mutations/megabase) was associated with improved OS (HR 0.58 [95% CI, 0.35-0.95]; P=0.03). In chemotherapy-treated patients (n=268), those with high APOBEC mutational signature had worse OS (HR 1.43 [95% CI, 1.06-1.94]; P=0.02). Neither FGFR3 mutations nor DNA damage-repair pathway alterations were associated with OS. A novel BIPI combining clinical and genomic variables (non-metastatic at initial diagnosis, normal or above normal albumin level at baseline, prior surgery for organ-confined disease, high TMB) identified ICI-treated patients with longest OS and was validated in an independent dataset.

CONCLUSIONS

Contemporary RWD including FoundationOne® CGP can be used to characterize outcomes in real-world patients according to biomarkers beyond PD-L1. A validated, novel clinico-genomic BIPI demonstrated satisfactory prognostic performance for OS in patients with mUC receiving front-line ICI therapy.

Real-world evidence of the effectiveness and safety of generic tofacitinib in rheumatoid arthritis patients: a retrospective, single-centre analysis from Western India

Generic tofacitinib has been available in India for more than a year and is widely used in rheumatoid arthritis (RA) therapy. There is scarce real-world data on its effectiveness and safety from India, especially given infection endemicity. We retrospectively analysed records (demographic and clinical information, haematology and biochemistry, adverse events) of patients prescribed generic tofacitinib from a single centre in Mumbai, India. Disease activity was calculated using the disease activity score-28 and erythrocyte sedimentation rate (DAS28-ESR) and other tools, and we used paired T-tests for significant response. We defined clinical tofacitinib failure as a composite outcome, including clinician’s decision to change to an alternative disease-modifying anti-rheumatic drug (DMARD) or flare after self-withdrawal. We performed logistic regression and survival analysis for determinants of clinical failure. We reviewed records of 102 patients (92 female; median age: 53 years) with mean RA duration of 146 months. Thirteen had prior treatment with innovator tofacitinib. There was significant improvement in disease activity parameters at a mean duration of 186 days. No serious adverse events were reported; 4 patients had tuberculosis and 19 patients had mild COVID-19 while on treatment. Clinical failure was seen in 25 patients, and mean time to failure on survival analysis was 357 days. No baseline characteristic predicted clinical failure. Generic tofacitinib showed good effectiveness and a tolerable adverse effect profile, despite tuberculosis endemicity and COVID-19. Setting up registries would be valuable in gaining more data on generic tofacitinib.

Key Points • There is scarce data from India regarding the use of tofacitinib in rheumatoid arthritis, despite widespread use. • In this retrospective analysis of 102 patients at a single centre, we found tofacitinib monotherapy was efficacious and tolerable. • Tuberculosis was detected in four and nineteen patients had mild covid.

Measuring the Effectiveness of Real-World Evidence to Ensure Appropriate Impact

The value of real-world evidence (RWE) in medicines regulation and health technology assessment has been increasingly emphasized. Nevertheless, although RWE is increasingly used, there has been limited systematic evidence of its value. A recent study that examined the role and impact of RWE in regulatory assessments conducted through the European Medicines Agency provided such evidence. Results of the study demonstrated RWE was important to decision making, particularly for certain questions such as the quantification of adverse events, the evaluation of risk minimization measures, and the assessment of product usage. The study suggested, however, that in many of the assessments further RWE would have been valuable and concluded that RWE has, as yet, played a limited role in hypothesis generation and in the assessment of medication effectiveness. This study had been possible only because of the transparency of the European Medicines Agency decision making. Ensuring transparency of RWE evidence collection, study design and conduct, and of decision making based on this evidence will facilitate further development of the uses and value of RWE. Keywords: benefit-risk assessment; medicines regulation; real-world evidence; regulatory decision making.

Impact of drug diversity on treatment effectiveness in relapsing-remitting multiple sclerosis (RRMS) in Germany between 2010 and 2018: real-world data from the German NeuroTransData multiple sclerosis registry

OBJECTIVE

To evaluate the impact of drug diversity on treatment effectiveness in relapsing-remitting multiple sclerosis (RRMS) in Germany.

DESIGN

This study employs real-world data captured in-time during clinical visits in 67 German neurology outpatient offices of the NeuroTransData (NTD) multiple sclerosis (MS) registry between 1 January 2010 and 30 June 2019, including 237 976 visits of 17 553 patients with RRMS. Adherence and clinical effectiveness parameters were analysed by descriptive statistics, time-to-event analysis overall and by disease-modifying therapies (DMTs) stratified by administration modes (injectable, oral and infusion). Three time periods were compared: 2010-2012, 2013-2015 and 2016-2018.

RESULTS

Between 2010 and 2018, an increasing proportion of patients with RRMS were treated with DMTs and treatment was initiated sooner after diagnosis of MS. Introduction of oral DMT temporarily induced higher readiness to switch. Comparing the three index periods, there was a continuous decrease of annualised relapse rates, less frequent Expanded Disability Status Scale (EDSS) progression and increasing periods without relapse, EDSS worsening and with stability of no-evidence-of-disease-activity 2 and 3 criteria, lower conversion rates to secondary progressive MS on oral and on injectable DMTs.

CONCLUSION

Sparked by the availability of new mainly oral DMTs, RRMS treatment effectiveness improved clinically meaningful between 2010 and 2018. As similar effects were seen for injectable and oral DMTs more than for infusions, a better personalised treatment allocation in many patients is likely. These results indicate that there is an overall beneficial effect for the whole patient with MS population as a result of the greater selection of available DMTs, a benefit beyond the head-to-head comparative efficacy, resulting from an increased probability and readiness to individualise MS therapy.

Guy's cancer cohort - real world evidence for cancer pathways

Background

The burden of disease due to cancer remains substantial. Since the value of real-world evidence has also been recognised by regulatory agencies, we established a Research Ethics Committee (REC) approved research database for cancer patients (Reference: 18/NW/0297).

Construction and content

Guy’s Cancer Cohort introduces the concept of opt-out consent processes for research in a subset of oncology patients diagnosed and treated at a large NHS Trust in the UK. From April 2016 until March 2017, 1388 eligible patients visited Guy’s and St Thomas’ NHS Foundation Trust (GSTT) for breast cancer management. For urological cancers this number was 1757 and for lung cancer 677. The Cohort consists of a large repository of routinely collected clinical data recorded both retrospectively and prospectively. The database contains detailed clinical information collected at various timepoints across the treatment pathway inclusive of diagnostic data, and data on disease progression, recurrence and survival.

Conclusions

Guy’s Cancer Cohort provides a valuable infrastructure to answer a wide variety of research questions of a clinical, mechanistic, and supportive care nature. Clinical research using this database will result in improved patient safety and experience. Guy’s Cancer Cohort promotes collaborative research and will accept applications for the release of anonymised datasets for research purposes.

Trial designs using real-world data: The changing landscape of the regulatory approval process

Purpose

There is a need to develop hybrid trial methodology combining the best parts of traditional randomized controlled trials (RCTs) and observational study designs to produce real‐world evidence (RWE) that provides adequate scientific evidence for regulatory decision‐making.

Methods

This review explores how hybrid study designs that include features of RCTs and studies with real‐world data (RWD) can combine the advantages of both to generate RWE that is fit for regulatory purposes.

Results

Some hybrid designs include randomization and use pragmatic outcomes; other designs use single‐arm trial data supplemented with external comparators derived from RWD or leverage novel data collection approaches to capture long‐term outcomes in a real‐world setting. Some of these approaches have already been successfully used in regulatory decisions, raising the possibility that studies using RWD could increasingly be used to augment or replace traditional RCTs for the demonstration of drug effectiveness in certain contexts. These changes come against a background of long reliance on RCTs for regulatory decision‐making, which are labor‐intensive, costly, and produce data that can have limited applicability in real‐world clinical practice.

Conclusions

While RWE from observational studies is well accepted for satisfying postapproval safety monitoring requirements, it has not commonly been used to demonstrate drug effectiveness for regulatory purposes. However, this position is changing as regulatory opinions, guidance frameworks, and RWD methodologies are evolving, with growing recognition of the value of using RWE that is acceptable for regulatory decision‐making.

Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis

BACKGROUND

Decision makers often need to assess the real-world effectiveness of new drugs prelaunch, when phase II/III randomized controlled trials (RCTs) but no other data are available.

OBJECTIVE

To develop a method to predict drug effectiveness prelaunch and to apply it in a case study in rheumatoid arthritis (RA).

METHODS

The approach 1) identifies a market-approved treatment ( S) currently used in a target population similar to that of the new drug ( N); 2) quantifies the impact of treatment, prognostic factors, and effect modifiers on clinical outcome; 3) determines the characteristics of patients likely to receive N in routine care; and 4) predicts treatment outcome in simulated patients with these characteristics. Sources of evidence include expert opinion, RCTs, and observational studies. The framework relies on generalized linear models.

RESULTS

The case study assessed the effectiveness of tocilizumab (TCZ), a biologic disease-modifying antirheumatic drug (DMARD), combined with conventional DMARDs, compared to conventional DMARDs alone. Rituximab (RTX) combined with conventional DMARDs was identified as treatment S. Individual participant data from 2 RCTs and 2 national registries were analyzed. The model predicted the 6-month changes in the Disease Activity Score 28 (DAS28) accurately: the mean change was -2.101 (standard deviation [SD] = 1.494) in the simulated patients receiving TCZ and conventional DMARDs compared to -1.873 (SD = 1.220) in retrospectively assessed observational data. It was -0.792 (SD = 1.499) in registry patients treated with conventional DMARDs.

CONCLUSION

The approach performed well in the RA case study, but further work is required to better define its strengths and limitations.

Synthesizing existing evidence to design future trials: survey of methodologists from European institutions

Background

‘Conditional trial design’ is a framework for efficiently planning new clinical trials based on a network of relevant existing trials. The framework considers whether new trials are required and how the existing evidence can be used to answer the research question and plan future research. The potential of this approach has not been fully realized.

Methods

We conducted an online survey among trial statisticians, methodologists, and users of evidence synthesis research using referral sampling to capture opinions about the conditional trial design framework and current practices among clinical researchers. The questions included in the survey were related to the decision of whether a meta-analysis answers the research question, the optimal way to synthesize available evidence, which relates to the acceptability of network meta-analysis, and the use of evidence synthesis in the planning of new studies.

Results

In total, 76 researchers completed the survey. Two out of three survey participants (65%) were willing to possibly or definitely consider using evidence synthesis to design a future clinical trial and around half of the participants would give priority to such a trial design. The median rating of the frequency of using such a trial design was 0.41 on a scale from 0 (never) to 1 (always). Major barriers to adopting conditional trial design include the current regulatory paradigm and the policies of funding agencies and sponsors.

Conclusions

Participants reported moderate interest in using evidence synthesis methods in the design of future trials. They indicated that a major paradigm shift is required before the use of network meta-analysis is regularly employed in the design of trials.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3449-6) contains supplementary material, which is available to authorized users.

Anti-androgen monotherapy versus gonadotropin-releasing hormone agonists in men with advanced, non-metastatic prostate cancer: a register-based, observational study

BACKGROUND

In randomised controlled trials, men with advanced, non-metastatic prostate cancer (PCa) treated with anti-androgen monotherapy (AA) had similar all-cause mortality as men treated with gonadotropin-releasing hormone (GnRH) agonists. Using real-world evidence (i.e., observational data), we aimed to further assess the difference in mortality between these two drug categories.

MATERIAL AND METHODS

We emulated a trial using data from Prostate Cancer data Base Sweden 3.0. We specifically focused on men diagnosed in 2006-2012 with high-risk PCa who had no distant metastasis. They either received primary hormonal therapy with AA (n = 2078) or GnRH agonists (n = 4878) who were followed for a median time of 5 years. Risk of death from PCa and other causes was assessed using competing risk analyses and Cox proportional hazards regression analyses, including propensity score matching.

RESULTS

The cumulative 5-year PCa mortality was lower for men treated with AA (16% [95% confidence interval, CI, 15-18%]) than men treated with GnRH agonists (22% [95% CI 21-24%]). The 5-year other cause mortality was also lower for men on AA (17% [95% CI 15-19%] compared to men on GnRH agonists (27% [95% CI 25-28%]). In regression analyses, the risk of PCa death was similar, GnRH agonists versus AA (reference), hazard ratio (HR) 1.08 (95% CI 0.95-1.23), but the risk of death from all causes was higher for men on GnRH agonists, HR 1.23 (95% CI 1.13-1.34). Consistent results were seen in the propensity score-matched cohort.

CONCLUSION

Our results indicate that the use of AA as primary hormonal therapy in men with high-risk non-metastatic PCa does not increase PCa-specific mortality compared to GnRH. Using AA instead of GnRH agonists may result in shorter time on/exposure to GnRH-treatment, which may reduce the risk of adverse events associated with this treatment.

Recognizing that Evidence is Made, not Born

Therapeutic product development, licensing and reimbursement may seem a well-oiled machine, but continuing high attrition rates, regulatory refusals, and patients' access issues suggest otherwise; despite serious efforts, gaps persist between stakeholders' stated evidence requirements and actual evidence supplied. Evidentiary deficiencies and/or human tendencies resulting in avoidable inefficiencies might be further reduced with fresh institutional cultures/mindsets, combined with a context-adaptable practices framework that integrates emerging innovations. Here, Structured Evidence Planning, Production, and Evaluation (SEPPE) posits that evidence be treated as something produced, much like other manufactured goods, for which "built-in quality" (i.e., "people" and "process") approaches have been successfully implemented globally. Incorporating proactive, iterative feedback-and-adjust loops involving key decision-makers at critical points could curtail avoidable evidence quality and decision hazards-pulling needed therapeutic products with high quality evidence of beneficial performance through to approvals. Critical for success, however, is dedicated, long-term commitment to systemic transformation.

Cognitive-Behavioral Analysis System of Psychotherapy, Drug, or Their Combination for Persistent Depressive Disorder: Personalizing the Treatment Choice Using Individual Participant Data Network Metaregression

BACKGROUND

Persistent depressive disorder is prevalent, disabling, and often difficult to treat. The cognitive-behavioral analysis system of psychotherapy (CBASP) is the only psychotherapy specifically developed for its treatment. However, we do not know which of CBASP, antidepressant pharmacotherapy, or their combination is the most efficacious and for which types of patients. This study aims to present personalized prediction models to facilitate shared decision-making in treatment choices to match patients' characteristics and preferences based on individual participant data network metaregression.

METHODS

We conducted a comprehensive search for randomized controlled trials comparing any two of CBASP, pharmacotherapy, or their combination and sought individual participant data from identified trials. The primary outcomes were reduction in depressive symptom severity for efficacy and dropouts due to any reason for treatment acceptability.

RESULTS

All 3 identified studies (1,036 participants) were included in the present analyses. On average, the combination therapy showed significant superiority over both monotherapies in terms of efficacy and acceptability, while the latter 2 treatments showed essentially similar results. Baseline depression, anxiety, prior pharmacotherapy, age, and depression subtypes moderated their relative efficacy, which indicated that for certain subgroups of patients either drug therapy or CBASP alone was a recommendable treatment option that is less costly, may have fewer adverse effects and match an individual patient's preferences. An interactive web app (https://kokoro.med.kyoto-u.ac.jp/CBASP/prediction/) shows the predicted disease course for all possible combinations of patient characteristics.

CONCLUSIONS

Individual participant data network metaregression enables treatment recommendations based on individual patient characteristics.

A multi-center, randomized controlled clinical trial, cost-effectiveness and qualitative research of electroacupuncture with usual care for patients with non-acute pain after back surgery: study protocol for a randomized controlled trial

BACKGROUND

Although pain after back surgery is known to be difficult to control, various treatment options are available to patients and physicians. A protocol for a confirmatory randomized controlled trial (RCT) on pain and function after back surgery was designed based on the results of a pilot trial. The aim of this study is to compare the effectiveness and safety of electroacupuncture (EA) with usual care (UC) versus UC alone on pain control and functional improvement after back surgery.

METHODS/DESIGN

This study is a multi-center, randomized, assessor-blinded trial with an active control conducted in conjunction with a cost-effectiveness analysis and qualitative research. Participants with non-acute low back pain with or without leg pain after back surgery who have a Visual Analogue Scale (VAS) pain intensity score ≥ 50 mm will be randomly assigned to either the EA with UC group (n = 54) or the UC group (n = 54). Following randomization, participants in both groups will receive the same UC treatment twice a week for a four-week treatment period. Participants assigned to the EA with UC group will additionally receive EA twice a week for the same four-week period. The primary outcome measure will be assessed using a VAS pain intensity score for low back pain. The secondary outcomes will include the Oswestry Disability Index, EuroQol 5-Dimension score, and drug intake. The primary and secondary outcomes will be measured at one, four, and eight weeks post randomization.

DISCUSSION

The results of this study will provide evidence of the effectiveness and cost-effectiveness of EA in managing postoperative pain following back surgery. In addition, the qualitative research results will help improve the quality of integrative medical interventions.

TRIAL REGISTRATION

Clinical Research Information Service (CRIS), Republic of Korea, KCT0001939 . Registered on 8 June 2016.

The development of CHAMP: a checklist for the appraisal of moderators and predictors

Background

Personalized healthcare relies on the identification of factors explaining why individuals respond differently to the same intervention. Analyses identifying such factors, so called predictors and moderators, have their own set of assumptions and limitations which, when violated, can result in misleading claims, and incorrect actions. The aim of this study was to develop a checklist for critically appraising the results of predictor and moderator analyses by combining recommendations from published guidelines and experts in the field.

Methods

Candidate criteria for the checklist were retrieved through systematic searches of the literature. These criteria were evaluated for appropriateness using a Delphi procedure. Two Delphi rounds yielded a pilot checklist, which was tested on a set of papers included in a systematic review on reinforced home-based palliative care. The results of the pilot informed a third Delphi round, which served to finalize the checklist.

Results

Forty-nine appraisal criteria were identified in the literature. Feedback was obtained from fourteen experts from (bio)statistics, epidemiology and other associated fields elicited via three Delphi rounds. Additional feedback from other researchers was collected in a pilot test. The final version of our checklist included seventeen criteria, covering the design (e.g. a priori plausibility), analysis (e.g. use of interaction tests) and results (e.g. complete reporting) of moderator and predictor analysis, together with the transferability of the results (e.g. clinical importance). There are criteria both for individual papers and for bodies of evidence.

Conclusions

The proposed checklist can be used for critical appraisal of reported moderator and predictor effects, as assessed in randomized or non-randomized studies using individual participant or aggregate data. This checklist is accompanied by a user’s guide to facilitate implementation. Its future use across a wide variety of research domains and study types will provide insights about its usability and feasibility.

Electronic supplementary material

The online version of this article (10.1186/s12874-017-0451-0) contains supplementary material, which is available to authorized users.

Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies

In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness.  There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models.  We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations.  No single "one-size-fits-all" approach is appropriate to assess the quality of modelling studies. The concept of the 'credibility' of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than 'risk of bias'.

Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies

In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness.  There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models.  We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations.  No single "one-size-fits-all" approach is appropriate to assess the quality of modelling studies. The concept of the 'credibility' of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than 'risk of bias'.