Problem
Ambiguity in communication of key study parameters limits the utility of real‐world evidence (RWE) studies in healthcare decision‐making. Clear communication about data provenance, design, ...analysis, and implementation is needed. This would facilitate reproducibility, replication in independent data, and assessment of potential sources of bias.
What We Did
The International Society for Pharmacoepidemiology (ISPE) and ISPOR–The Professional Society for Health Economics and Outcomes Research (ISPOR) convened a joint task force, including representation from key international stakeholders, to create a harmonized protocol template for RWE studies that evaluate a treatment effect and are intended to inform decision‐making. The template builds on existing efforts to improve transparency and incorporates recent insights regarding the level of detail needed to enable RWE study reproducibility. The overarching principle was to reach for sufficient clarity regarding data, design, analysis, and implementation to achieve 3 main goals. One, to help investigators thoroughly consider, then document their choices and rationale for key study parameters that define the causal question (e.g., target estimand), two, to facilitate decision‐making by enabling reviewers to readily assess potential for biases related to these choices, and three, to facilitate reproducibility.
Strategies to Disseminate and Facilitate Use
Recognizing that the impact of this harmonized template relies on uptake, we have outlined a plan to introduce and pilot the template with key international stakeholders over the next 2 years.
Conclusion
The HARmonized Protocol Template to Enhance Reproducibility (HARPER) helps to create a shared understanding of intended scientific decisions through a common text, tabular and visual structure. The template provides a set of core recommendations for clear and reproducible RWE study protocols and is intended to be used as a backbone throughout the research process from developing a valid study protocol, to registration, through implementation and reporting on those implementation decisions.
Aim
To estimate risks of diabetic ketoacidosis (DKA), acute liver injury (ALI), acute kidney injury (AKI), chronic kidney disease (CKD), severe complications of urinary tract infection (UTI) and ...genital infection (GI) among patients with type 2 diabetes initiating empagliflozin versus those initiating a dipeptidyl peptidase‐4 (DPP‐4) inhibitor.
Materials and Methods
In this large multinational, observational, new‐user cohort study in UK, Danish and US healthcare data sources, patients initiated empagliflozin or a DPP‐4 inhibitor between August 2014 and August 2019, were aged ≥18 years, and had ≥12 months' continuous health plan enrolment. Incidence rates by exposure and incidence rate ratios, adjusted for propensity‐score deciles, were calculated.
Results
In total, 64 599 empagliflozin initiators and 203 315 DPP‐4 inhibitor initiators were included. There was an increased risk pooled adjusted incidence rate ratios (95% confidence interval) of DKA 2.19 (1.74‐2.76) and decreased risks of ALI 0.77 (0.50‐1.19) in patients without predisposing conditions of liver disease; 0.70 (0.56‐0.88) in all patients and AKI 0.54 (0.41‐0.73). In the UK data, there was an increased risk of GI males: 4.04 (3.46‐4.71); females: 3.24 (2.81‐3.74) and decreased risks of CKD 0.53 (0.43‐0.65) and severe complications of UTI 0.51 (0.37‐0.72). The results were generally consistent in subgroup and sensitivity analyses.
Conclusions
Compared with DDP‐4 inhibitor use, empagliflozin use was associated with increased risks of DKA and GI and decreased risks of ALI, AKI, CKD and severe complications of UTI. These associations are consistent with previous studies and known class effects of sodium‐glucose cotransporter 2 inhibitors, including renoprotective effects and beneficial effects on alanine aminotransferase levels.
Purpose
To evaluate availability of spirometry and symptom data in the Clinical Practice Research Datalink (United Kingdom) to assess COPD severity using the Global Initiative for Chronic Obstructive ...Lung Disease (GOLD) 2016 definition and comparing it with an algorithm used in other studies.
Methods
This was a descriptive, noninterventional, secondary database cohort study of patients with COPD aged 40 years or older, who initiated treatment with specific COPD medications. Patients were classified according to COPD severity (1) in GOLD 2016 “ABCD” categories based on symptoms (Medical Research Council dyspnea grade, COPD Assessment Test, breathlessness), percent predicted FEV1, and exacerbation history and (2) as mild, moderate, severe, or very severe based on treatment and exacerbation history.
Results
The study included 63 900 patients with COPD aged 40 years or older that were new users of 1 or more COPD medication of interest. Percent predicted FEV1 was available for 80.9% of patients; symptoms for 75.6% of patients. Classification into GOLD 2016 ABCD categories was possible for 75.6% of the patients. The GOLD 2016 ABCD definition classified more patients under the high‐risk categories (22.1%, A; 18.8%, B; 21.3%, C; 37.9%, D) than did the adapted algorithm (7.9%, mild; 48.6%, moderate; 42.1%, severe; 1.4%, very severe).
Conclusion
Using our adaptation of the GOLD 2016 COPD severity classification, the information in the Clinical Practice Research Datalink allowed us to ascertain COPD severity in approximately 75% of patients with COPD. Algorithms that include medication use tend to misclassify patients with the extreme COPD severity categories.
Purpose
Validating cases of acute liver injury (ALI) in health care data sources is challenging. Previous validation studies reported low positive predictive values (PPVs).
Methods
Case validation ...was undertaken in a study conducted from 2009 to 2014 assessing the risk of ALI in antidepressants users in databases in Spain (EpiChron and SIDIAP) and the Danish National Health Registers. Three ALI definitions were evaluated: primary (specific hospital discharge codes), secondary (specific and nonspecific hospital discharge codes), and tertiary (specific and nonspecific hospital and outpatient codes). The validation included review of patient profiles (EpiChron and SIDIAP) and of clinical data from medical records (EpiChron and Denmark). ALI cases were confirmed when liver enzyme values met a definition by an international working group.
Results
Overall PPVs (95% CIs) for the study ALI definitions were, for the primary ALI definition, 84% (60%‐97%) (EpiChron), 60% (26%‐88%) (SIDIAP), and 74% (60%‐85%) (Denmark); for the secondary ALI definition, 65% (45%‐81%) (EpiChron), 40% (19%‐64%) (SIDIAP), and 70% (64%‐77%) (Denmark); and for the tertiary ALI definition, 25% (18%‐34%) (EpiChron), 8% (7%‐9%) (SIDIAP), and 47% (42%‐52%) (Denmark). The overall PPVs were higher for specific than for nonspecific codes and for hospital discharge than for outpatient codes. The nonspecific code “unspecified jaundice” had high PPVs in Denmark.
Conclusions
PPVs obtained apply to patients using antidepressants without preexisting liver disease or ALI risk factors. To maximize validity, studies on ALI should prioritize hospital specific discharge codes and should include hospital codes for unspecified jaundice. Case validation is required when ALI outpatient cases are considered.
Purpose
Strategies to identify and validate acute myocardial infarction (AMI) and stroke in primary‐care electronic records may impact effect measures, but to an unknown extent. Additionally, the ...validity of cardiovascular risk factors that could act as confounders in studies on those endpoints has not been thoroughly assessed in the United Kingdom Clinical Practice Research Datalink's (CPRD's) GOLD database. We explored the validity of algorithms to identify cardiovascular outcomes and risk factors and evaluated different outcome‐identification strategies using these algorithms for estimation of adjusted incidence rate ratios (IRRs).
Methods
First, we identified AMI, stroke, smoking, obesity, and menopausal status in a cohort treated for overactive bladder by applying computerized algorithms to primary care medical records (2004–2012). We validated these cardiovascular outcomes and risk factors with physician questionnaires (gold standard for this analysis). Second, we estimated IRRs for AMI and stroke using algorithm–identified and questionnaire–confirmed cases, comparing these with IRRs from cases identified through linkage with hospitalization/mortality data (best estimate).
Results
For AMI, the algorithm's positive predictive value (PPV) was >90%. Initial algorithms for stroke performed less well because of inclusion of codes for prevalent stroke; algorithm refinement increased PPV to 80% but decreased sensitivity by 20%. Algorithms for smoking and obesity were considered valid. IRRs based on questionnaire‐confirmed cases only were closer to IRRs estimated from hospitalization/mortality data than IRRs from algorithm‐identified cases.
Conclusions
AMI, stroke, smoking, obesity, and postmenopausal status can be accurately identified in CPRD. Physician questionnaire–validated AMI and stroke cases yield IRRs closest to the best estimate.
Background
Many factors contribute to developing and conducting a successful multi‐data source, non‐interventional, post‐authorization safety study (NI‐PASS) for submission to multiple health ...authorities. Such studies are often large undertakings; evaluating and sharing lessons learned can provide useful insights to others considering similar studies.
Objectives
We discuss challenges and key methodological and organizational factors that led to the delivery of a successful post‐marketing requirement (PMR)/PASS program investigating the risk of cardiovascular and cancer events among users of mirabegron, an oral medication for the treatment of overactive bladder.
Results
We provide context and share learnings, including sections on research program collaboration, scientific transparency, organizational approach, mitigation of uncertainty around potential delays, validity of study outcomes, selection of data sources and optimizing patient numbers, choice of comparator groups and enhancing precision of estimates of associations, potential confounding and generalizability of study findings, and interpretation of results.
Conclusions
This large PMR/PASS program was a long‐term commitment from all parties and benefited from an effective coordinating center and extensive scientific interactions across research partners, scientific advisory board, study sponsor, and health authorities, and delivered useful learnings related to the design and organization of multi‐data source NI‐PASS.
Purpose
Acute liver injury (ALI) is an important adverse drug reaction. We estimated the positive predictive values (PPVs) of ICD‐10‐GM codes of ALI used in an international postauthorisation safety ...study (PASS).
Methods
Analyses used routine data (2007 to 2016, adults) from a German academic hospital in a cross‐sectional design. Two algorithms from the PASS were applied to extract potential cases from the hospital information system: specific end point (A) (discharge diagnosis of liver disease–specific codes) and less specific end point (B) (discharge and outpatient‐specific and nonspecific codes suggestive of liver injury). ALI cases were confirmed on the basis of plasma liver enzyme activity elevation. Secondary analysis was performed following exclusion of cases with known cancer, chronic liver, biliary and pancreatic disease, heart failure, and alcohol‐related disorders, as applied in the PASS.
Results
On the basis of ICD codes: outcome A, 154 cases (143 with case notes and lab data for case verification); outcome B, 485 cases (357 with case notes and lab data). ALI was confirmed in 71 outcome A cases, PPV of 49.7% (95% confidence interval CI, 41.2%‐58.1%), and 100 outcome B cases, PPV of 28.0% (95% CI, 23.4%‐33.0%). Applying exclusion criteria increased PPV (95% CI) to 62.7% (50.0%‐74.2%) for outcome A and 45.7% (37.2%‐54.3%) for outcome B.
Conclusions
In safety studies on hepatotoxicity based on routine data using ICD‐10‐GM discharge codes and when validation of potential cases is not feasible, only the more specific codes should be used to describe ALI, and competing diagnoses for liver injury should be excluded to avoid substantial misclassification.
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