A document by Juan Hincapie-Castillo. Click on the document to view its contents.

Purpose: With the expansion of research utilizing electronic healthcare data to identify transgender (TG) population health trends, the validity of computational phenotype algorithms to identify TG patients is not well understood. We aim to identify the current state of the literature that has utilized CPs to identify TG people within electronic healthcare data and their validity, potential gaps, and a synthesis of future recommendations based on past studies. Methods: Authors searched the National Library of Medicine’s PubMed, Scopus, and the American Psychological Association Psyc Info’s databases to identify studies published in the United States that applied CPs to identify TG people within electronic health care data. Results: Twelve studies were able to validate or enhance the positive predictive value (PPV) of their CP through manual chart reviews (n=5), hierarchy of code mechanisms (n=4), key text-strings (n=2), or self-surveys (n=1). CPs with the highest PPV to identify TG patients within their study population contained diagnosis codes and other components such as key text-strings. However, if key text-strings were not available, researchers have been able to find most TG patients within their electronic healthcare databases through diagnosis codes alone. Conclusion: CPs with the highest accuracy to identify TG patients contained diagnosis codes along with components such as procedural codes or key text-strings. CPs with high validity are essential to identifying TG patients when self-reported gender identity is not available. Still, self-reported gender identity information should be collected within electronic healthcare data as it is the gold standard method to better understand TG population health patterns.

A document by Liza Gibbs R. Click on the document to view its contents.

Purpose To describe utilization patterns, characteristics of users and prescriber responsibility of the new oral antiviral medication, molnupiravir, indicated for mild-to-moderate COVID-19. Methods Using nationwide registries, we identified all Danish adults who filled a prescription for molnupiravir from December 16 th, 2021, to August 31 st, 2022. We described weekly incidence rates and patient characteristics over time, prescriber responsibility as well as time between molnupiravir initiation and a positive SARs-CoV-2 test. Patient characteristics were compared to an untreated SARS-CoV-2 positive cohort. Results By August 31 st, 2022, 5,847 individuals had filled a prescription for molnupiravir. The incidence rate gradually increased to 2,000 weekly prescriptions per 100,000 RT-PCR SARS-CoV-2 positives. Users of molnupiravir were most often men (55% vs. 45% women). The majority (81%) had a positive RT-PCR SARS-CoV-2 test and few (2.9%) redeemed molnupiravir outside the recommended window of 5 days from the positive test result. Compared to an untreated SARS-CoV-2 positive cohort, users of molnupiravir had a median age of 74 years vs. 44 years, a higher proportion resided in a nursing home (12% vs. 1.1%) and had a higher number of comorbidities (median of 3 vs. 0); most commonly hypertension (38%), chronic lung disease (35%), diabetes (20%) and mood disorders (20%). General practitioners were the primary prescribers of molnupiravir (91%). Conclusions Molnupiravir was mainly prescribed by general practitioners to RT-PCR SARS-CoV-2 positive individuals who had a potentially increased risk of severe COVID-19. Though some off-label prescribing occurred, our study indicates a high level of adherence to contemporary guidelines.

Purpose: Reducing initial exposure of “opioid naïve” patients to opioids is a public health priority. Identifying opioid naïve patients is difficult, as numerous definitions are used. The objective is to summarize current definitions and evaluate their impact on opioid naïve measures in Alberta. Methods: Using dispense data (2017-2021) and definitions guided by a scoping review, we determined the number of “opioid naïve” patients using descriptive analyses. Three definitions were identified: 1) no opioid use within the previous 30 days/6 months/1 year, based on dispensation date; 2) definition 1, based on dispensation date plus days of supply; 3) exclusion of codeine from definitions 1 and 2. Results: Of over a dozen definitions of opioid naïve identified in the scoping review, most used an ‘opioid free’ period (commonly 30 days/6 months/1 year). Other definitions included “availability of drug” based on days of supply and/or excluded certain opioid products. Approximately 36.4% of Albertans (n=1,551,075) had an opioid dispensation in 2017-2021. The average age was 46.6±18.8 and 52.8% were female. Results were most affected by the “opioid free” period, with 97.4%, 83.2% and 65.6% being classified as opioid naïve using time windows from definition 1. Definitions 2 and 3 did not materially change the results. Conclusions: The most convenient definition for “opioid naïve” was definition 1 using a 1-year window, which aligns with the Canadian Institutes for Health Information definition. Irrespective of definition used, a large proportion of opioid users would be considered opioid naïve despite initiatives to curb opioid prescription in Alberta.

Authors:Alecia Clary , Ph.D., MSW (AC) (Corresponding author)Affiliation: The Reagan-Udall Foundation for the FDA, Washington, DC, USA Address: 1333 New Hampshire Ave, NW Suite 420, Washington DC 20036, USA Email: [email protected] Phone: 202-849-2075 ORCID ID: 0000-0002-7774-9808Nancy D Lin , (NDL) Affiliation: IQVIA Real World Solutions, Bridgewater, NJ, USA Address: 77 Corporate Drive, Bridgewater, NJ 08807 Email: [email protected] Lasky , (TL) Affiliation: The United States Food and Drug Administration, Office of Data, Analytics, & Research, Office of the Commissioner, Washington DC, USA Address: 10903 New Hampshire Avenue, Silver Spring, MD, USA. Email: [email protected] W Reynolds , (MR) Affiliation: IQVIA Real-World Solutions, Washington, DC, USA Address: 201 Broadway, Cambridge, MA, USA. Email: [email protected] Chokkalingam , (ACH) Affiliation: Gilead Sciences, Foster City, California, USA Address: 333 Lakeside Drive Email: [email protected] Rodriguez-Watson, (CRW)Affiliation: The Reagan-Udall Foundation for the FDA, Washington, DC, USA Address: 1333 New Hampshire Ave, NW Suite 420, Washington DC 20036, USA Email: [email protected] paper has not been previously printed, currently has not been submitted for publication in any other journal and is not pending acceptance in any other journal. We have not had any prior correspondence with the journal about the manuscript.

Purpose The generation of representative disease phenotypes is important for ensuring the reliability of the findings of observational studies. The aim of this manuscript is to outline a reproducible framework for reliable and traceable phenotype generation based on real world data for use in the Data Analysis and Real-World Interrogation Network (DARWIN EU®). We illustrate the use of this framework by generating phenotypes for two complex diseases: pancreatic cancer and systemic lupus erythematosus (SLE). Methods The phenotyping process involves a 14-step process based on a standard operating procedure co-created by the DARWIN EU® Coordination Centre in collaboration with the European Medicines Agency. A number of bespoke R packages were utilised to generate and review codelists for two phenotypes based on real world data mapped to the OMOP Common Data Model. Results Phenotypes were generated for both pancreatic cancer and SLE, and cohorts were generated using the Clinical Practice Research Datalink (UK primary care records) and Pharmetrics (US health claims data). Diagnostic checks were performed, which showed these cohorts had broadly similar incidence and prevalence figures to previously published literature. Additionally, co-occurrent symptoms, conditions, and medication use were in keeping with pre-specified clinical descriptions based on previous knowledge. Conclusions Our detailed phenotyping process makes use of bespoke tools and allows for comprehensive codelist generation and review, as well as large-scale exploration of the characteristics of the generated cohorts. Wider use of structured phenotyping methods will be important in ensuring the reliability of observational studies for regulatory purposes.

Purpose: To explore the differences among erectile aids (i.e., phosphodiesterase type 5 inhibitors [PDE5i] and intracavernousal drugs) of the relative risk of priapism and identify age groups at risk. Methods: We queried the World Health Organization global database of individual case safety reports (VigiBase) for records of the ADR with sildenafil, tadalafil, avanafil, vardenafil, papaverine, and alprostadil. Disproportionality analyses (case/non-case approach) were performed to assess the relative risk of priapism reporting in PDE5i consumers compared to intracavernousal drug recipients. Results: From a total of 133,819 ADR events for erectogenic medications, 632 were priapism (PDE5is: n=550, 0.41%; intracavernousal drugs: n=82, 9.92%). We observed a strong signal for priapism induction for intracavernousal drugs than PDE5is (reporting odds ratio [ROR]=34.7; confidence interval [CI] 95%: 27.12 - 43.94 vs. ROR= 1.38; CI 95%: 1.24 - 1.54). For all PDE5i agents, the 12-17 years age group had the highest highest ROR (ROR=9.49, CI 95%: 3.76 - 19.93) followed by 2-11 years (ROR=4.31, CI 95%: 1.57 - 9.4). Disproportionality signals for consumers under eighteen for both all PDE5is as a whole (ROR=4.57, CI 95%: 2.48 - 7.73) and sildenafil (ROR=4.89, CI 95%: 2.51 - 8.62) were significantly stronger than individuals eighteen or older (ROR=1.06, CI 95%: 0.93 - 1.21 and ROR=1.08, CI 95%: 0.91 - 1.26, respectively). Conclusions: While the overall risk of priapism following the oral administration of PDE5is is extremely low compared with intracavernousal remedies, adolescents are at a higher risk of priapism than older men.

Purpose: Sickle cell disease (SCD) affects all organ systems and is characterized by numerous acute and chronic complications and comorbidities. Standardized codes are needed for complications/comorbidities used in real-world evidence (RWE) studies that rely on administrative and medical coding. This systematic literature review was conducted to produce a comprehensive list of complications/comorbidities associated with SCD, along with their diagnosis codes used in RWE studies. Methods: A search in MEDLINE and Embase identified studies published from 2016-2023. Studies were included if they were conducted in US SCD populations and reported complications/comorbidities and respective International Classification of Diseases, Clinical Modification (ICD-CM) codes. All identified complications/comorbidities and codes were reviewed by a certified medical coding expert and hematologist. Results: Of 1,851 identified studies, 40 were included. The most reported complications/comorbidities were stroke, acute chest syndrome, pulmonary embolism, venous thromboembolism, vaso-occlusive crisis, and priapism. Most of the studies used ICD-9-CM codes (n=21), while some studies used ICD-10-CM codes (n=3) or both (n=16), depending on the study period. Most codes reported in literature were heterogeneous across complications/comorbidities. The medical coding expert recommended modifications for several conditions. Conclusion: While many studies we identified did not report their codes and were excluded from this review, the studies with codes exhibited diverse coding definitions. By providing a standardized set of diagnosis codes that were reported by studies and reviewed by a coding expert and hematologist, our review can serve as a foundation for accurately identifying complications/comorbidities in future research, and may reduce heterogeneity, enhance transparency, and improve reproducibility.

Purpose: In drug studies, research designs requiring no prior exposure to certain drug classes may restrict important populations. Since abuse-deterrent formulations (ADF) of opioids are routinely prescribed after other opioids, choice of study design, identification of appropriate comparators, and addressing confounding by “indication” are important considerations in ADF post-marketing studies. Methods: In a retrospective cohort study using claims data (2006-2018) from a North Carolina private insurer [NC claims] and Merative MarketScan [MarketScan], we identified patients (18-64 years old) initiating ADF or non-ADF extended-release/long-acting (ER/LA) opioids. We compared patient characteristics and described opioid treatment history between treatment groups, classifying patients as traditional (no opioid claims during prior six-month washout period) or prevalent new users. Results: We identified 8,415 (NC claims) and 147,978 (MarketScan) ADF, and 10,114 (NC claims) and 232,028 (MarketScan) non-ADF ER/LA opioid initiators. Most had prior opioid exposure (ranging 64-74%), and key clinical differences included higher prevalence of recent acute or chronic pain and surgery among patients initiating ADFs compared to non-ADF ER/LA initiators. Concurrent immediate-release opioid prescriptions at initiation were more common in prevalent new users than traditional new users. Conclusions: Careful consideration of the study design, comparator choice, and confounding by “indication” is crucial when examining ADF opioid use-related outcomes.

Purpose: While much has been written about how distributed networks address internal validity, external validity is rarely discussed. We aimed to define key terms related to external validity, discuss how they relate to distributed networks, and identify how three networks (the US Food and Drug Administration’s Sentinel System, the Canadian Network for Observational Drug Effect Studies [CNODES], and PCORnet, the National Patient Centered Clinical Research Network, initiated and supported by the Patient-Centered Outcomes Research Institute. Methods: We define external validity, target populations, target validity, generalizability, and transportability and describe how each relates to distributed networks. We then describe Sentinel, CNODES, and PCORnet and how each approaches these concepts. Results: Each network approaches external validity differently Sentinel answers regulatory questions in the general US population using data from commercial health plans and Medicare fee-for-service beneficiaries and considers external validity when exploring outliers or performing subgroup analyses to examine potential heterogeneity of treatment effects. CNODES focuses on a Canadian target population but includes UK and US data and thus has to make decisions about which partners can be included in each analysis. PCORnet supports a wider array of studies including randomized trials and often assesses whether a given study will be representative of the wider US population. Conclusions: There is no one-size-fits-all approach to external validity within distributed networks. With these networks and comparisons between their findings becoming a key part of pharmacoepidemiology, there is a need to adapt tools for improving external validity to the distributed network setting.

Purpose: There is increasing recognition of the importance of transparency and reproducibility in scientific research. This study aimed to quantify the extent to which programming code is publicly shared in pharmacoepidemiology, and to develop a set of recommendations on this topic. Methods: We conducted a literature review identifying all studies published in “Pharmacoepidemiology and Drug Safety” (PDS) between 2017 and 2022, Data was extracted on the frequency and types of programming code shared, and other key open science practices (clinical codelist sharing, data sharing, study pre-registration, and use of reporting guidelines). We developed six recommendations for investigators who choose to share to programming code and gathered feedback from members of the International Society of Pharmacoepidemiology (ISPE). Results: Programming code sharing by articles published in PDS ranged from 2.4% in 2017 to 13.4% in 2022. It was more prevalent among articles with a methodological focus, simulation studies, and papers which also shared record-level data. We recommend that reporting of open science practices, including code sharing, is standardised to enable continued monitoring. When sharing programming code, we recommend the use of permanent digital identifiers, appropriate licenses, and, where possible, adherence to good software practices around the provision of metadata and documentation, computational reproducibility, and data privacy. Conclusion: Programming code sharing is rare but increasing in pharmacoepidemiology studies published in Pharmacoepidemiology and Drug Safety. We recommend improved and consistent reporting of code sharing, and adherence to good programming practices in order to maximize the utility of code when this is shared.

Comparing causal effect estimates obtained using observational data to those obtained from the gold standard (i.e., randomized controlled trials, RCTs) helps us assess the validity of these estimates. However, comparisons are challenging due to differences between observational data and RCT generated data: First, the treatment assignment mechanism is often unknown for observational data, and second, the sampling mechanism often differs between the RCT and the observational data. Differences in the treatment assignment mechanism introduce potential confounding, whereas differences in the sampling mechanism introduce sampling bias. This article proposes a two-step framework for the validation of causal effect estimates obtained from observational data by adjusting for both mechanisms. A simulation study is conducted to show that our suggested two-step framework enables observational data to produce causal effect estimates similar to those of an RCT. An application of our approach to validate treatment effects of adjuvant chemotherapy obtained from registry data is demonstrated. This article establishes a novel framework for comparing causal effect estimates between observational data and RCT data, facilitating the assessment of the validity of causal effect estimates obtained from observational data.

Pharmacoepidemiology and Drug Safety’s Core Concepts in Pharmacoepidemiology Section at One Year: Where Do We Go from Here? Jennifer L. Lund,1,2 Vincent Lo Re III3,41University of North Carolina at Chapel Hill, Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, NC, USA2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA3Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA4Division of Epidemiology, Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USARunning title: Core Concepts in Pharmacoepidemiology – Year 2Conflicts of interest: The authors report no conflicts of interest.Acknowledgements: The authors appreciated the critical input on the Core Concepts in Pharmacoepidemiology section from Brian Strom, Olaf Klungel, BJ Park, and the members of the International Society for Pharmacoepidemiology’s Publications and Communications Committee, particularly Elena Rivero, Patricia Saddier, Joan Largent, and Blànaid Hicks.

Purpose Exposure of hydrochlorothiazide (HCTZ) has been linked to the increase of skin cancer in the Caucasian population, especially for the squamous cell carcinoma (SCC) but not for basal cell carcinoma (BCC). This study aimed to evaluate the risks of skin cancer between patients receiving HCTZ and those receiving other antihypertensives. Methods This retrospective cohort study was derived from the National Health Insurance Database in Taiwan. We enrolled patients aged 20 years and older who newly receiving antihypertensive medications between 2004 - 2015. We calculated the medication possession ratio (MPR) of the first two years of treatment for patient enrollment and treatment classification, in which patients with MPR above 80% were enrolled and patients were subsequently categorized into receiving HCTZ, other thiazide diuretics, non-thiazide diuretics, and non-diuretic antihypertensives. The Cox proportional hazards model was used to evaluate the risk of skin cancer, and further divided into SCC, and BCC. Results Our study enrolled 41,086, 27,402, 19,613, and 856,782 patients receiving HCTZ, other thiazide diuretics, non-thiazide diuretics, and non-diuretic antihypertensives, respectively. We found BCC risks were similar when comparing HCTZ with other thiazides (adjusted hazard ratio, 0.84; 95% CI: 0.54-1.33), non-thiazide diuretics (0.93; 0.51-1.67), and non-diuretic antihypertensives (0.91; 0.66-1.26). Higher SCC risk was observed in the HCTZ group, compared to other thiazide (1.24; 0.74-2.08), non-thiazide diuretics (1.32; 0.70- 2.51), and non-diuretic antihypertensives (1.23; 0.87-1.73), although the differences were not statistically significant. Conclusions We conclude that skin cancer need not be of major concern to physicians when prescribing antihypertensives for an Asian population.

Barbro Westerholm, 1933-2023

Purpose Pregnancies ending before gestational week 12 are common but not notified to the Medical Birth Registry of Norway. Our goal was to develop an algorithm that more completely detects and dates pregnancy outcomes by using diagnostic codes from primary and secondary care registries to complement information from the birth registry. Methods We used nationwide linked registry data between 2008 and 2018 in a hierarchical manner: We developed an algorithm to arrive at unique pregnancy outcomes, considering codes within 56 days as the same event. To infer gestational age of pregnancy outcomes before gestational week 12, we used the median gestational week of pregnancy markers (45 ICD-10 codes and 9 ICPC-2 codes). When no pregnancy markers were available, we assigned outcome-specific gestational age estimates. The performance of the algorithm was assessed by blinded clinicians. Results Using only the medical birth registry, we identified 649,703 pregnancies, including 1,369 (0.2%) miscarriages and 3,058 (0.5%) elective terminations. With the new algorithm, we detected 859,449 pregnancies, including 642,712 live-births (74.8%), 112,257 miscarriages (13.1%), 94,664 elective terminations (11.0%), 6,429 ectopic pregnancies (0.7%), 2,564 stillbirths (0.3%), and 823 molar pregnancies (0.1%). The median gestational age was 10 +0 weeks (IQR 10 +0-11 +3) for miscarriages and 8 +0 weeks (IQR 8 +0-9 +6) for elective terminations. Gestational age could be inferred using pregnancy markers for 66.3% of miscarriages and 47.2% of elective terminations. Conclusion The pregnancy algorithm improved the detection and dating of early non-live pregnancy outcomes that would have gone unnoticed if relying solely on the medical birth registry information.

Background: Adverse drug events (ADEs) are a frequent cause of injury in patients. Our aim was to assess pharmacist interventions and their association with ADEs and potential adverse drug events (PADE). Methods: The search criteria: a published RCT, evidence of a pharmacist intervention, a comparison control group, and measurement of ADEs or PADEs. The information sources included MEDLINE, Embase, and two other databases through September 19, 2022. The risk of bias was assessed using the Cochrane tool for RCTs. A random-effects model for pooled studies was employed Results: Fifteen references meeting inclusion criteria were discovered. For ADEs, the pooled results showed a statistically significant benefit of pharmacist intervention in comparison to the control group (RR = 0.86; [95% CI 0.80-0.94); P = 0.0005. The heterogeneity was insignificant (P = 0.72; I 2 = 0%). Patients receiving a pharmacist intervention were 14% less likely for ADE than those who did not receive a pharmacist intervention. The estimated number of patients needed to prevent one ADE across all patient locations was 33. For PADEs, the pooled results did not show a statistically significant benefit for pharmacist intervention in comparison to the control group (RR = 0.79; [95% CI 0.47 – 1.32]; P =0.37.There was substantial heterogeneity in the pooled studies (P = 0.01; I 2 = 77%). However, there was a statistically significant subgroup difference (P = 0.005) for the intervention type. Conclusions: To our knowledge, this is the first systematic review and meta-analysis of RCTs seeking to understand the association of pharmacist interventions with ADEs and PADEs. The risk of having an ADE is reduced by a seventh for patients receiving a pharmacist care intervention versus no such intervention. This fraction could be higher for certain high-risk patients. The estimated number of patients needed to be followed across all patient locations to prevent one preventable ADE across all patient locations is 33. Also, a subgroup analysis of pharmacist intervention focus suggests that further research is necessary to fully understand the impact of TOC pharmacist intervention on PADEs. If validated, these findings have potential to significantly reduce drug-related morbidity and related healthcare costs.