Anna-Maija Tolppanen

Background: Target trial emulation (TTE) studies are increasingly important for regulatory decision‑making and health technology assessments (HTAs), but current risk-of-bias (RoB) tools are not specifically tailored to assess biases central to TTE studies—such as immortal time bias, misaligned eligibility criteria, and prevalent user bias. RoB assessment for TTE studies thus remains difficult, and it is unclear which tools and adaptations researchers currently use or how well they work. Objective: This study aims to analyze the RoB assessment of TTE studies at regulatory and policy decision points along the medical product life cycle by providing a systematic overview of tools developed, used, adapted, or evaluated for TTE studies and the perceived importance and feasibility of assessing TTE studies by HTA assessors, regulators, systematic reviewers, and methods experts. Methods: This is a protocol for a scoping review and online survey among systematic reviewers, methods experts, European HTA organizations, and regulators. We will collect data on the name, description, and feasibility of RoB tools used, adapted, and developed for TTE studies, as well as RoB assessment results and the RoB sources relevant for TTE studies. Two authors will use qualitative content analysis to analyze the data independently. The systematic search for published and gray literature in 4 electronic databases (PubMed, Scopus, Web of Science, and the Cochrane Library), on relevant websites (eg, Cochrane, HTA and regulatory agencies), and through reference list checking was conducted in May to June 2026. Results: As of August 25, 2026, screening is ongoing, and 78 references have been preliminarily included in the scoping review. We will analyze the scoping review and survey data and provide an overview of the types, feasibility, and assessment results of RoB tools currently used, adapted, or developed for TTE studies, as well as the RoB sources considered relevant for TTE studies by HTA assessors, regulators, systematic reviewers, and methods experts. Analysis results of the literature review and survey are expected in September 2026 and November 2026, respectively. Conclusions: The analysis of the scoping review and survey data will inform users of TTE evidence about the feasibility of RoB tools; future development and training needs; and the perceived value of assessing the RoB in HTAs, regulatory decisions, and systematic reviews. International Registered Report Identifier (IRRID): DERR1-10.2196/107499

Background: Several Alzheimer's disease (AD) clinical trials currently focus on drug repurposing. Machine learning (ML)-based pharmacoepidemiological approaches may help identify candidate drugs for trials. Objective: We applied an ML-based signal detection method to identify drugs associated with AD risk. Methods: Using Finnish nationwide register-based data, we defined drug exposure at both subgroup and drug substance levels according to the Anatomical Therapeutic Chemical classification. Three binary embedded variables were calculated for each drug based on the frequency of dispensations over three years, starting 10 years before the index date. An algorithm combining subsampling and lasso-logistic regression was applied, with 500 replications for each drug exposure variable. Drug variables with a selection percentage (SP) ≥ 70% across replications were considered as signals. The average beta describes the direction and strength of the association. Results: The study population comprised 43,926 AD cases and 43,926 matched controls. The mean age was 80.3 years in both groups, and 65% of participants were women. Four drug subgroups and three individual drugs were associated with a lower risk of AD, whereas 14 subgroups and 11 individual drugs were associated with a higher risk. Drugs associated with decreased AD risk belonged to cardiovascular drugs: antihypertensives affecting the renin-angiotensin and diuretics. Conclusions: The identified associations are consistent with established risk factors of AD and support the importance of effective hypertension management in AD prevention. Further studies are needed to evaluate whether antihypertensive drugs may exert neuroprotective effects and represent viable candidates for drug repurposing in AD.

Real‐world data are increasingly important for regulatory and health technology assessment decision‐making, yet their effective use across Europe remains limited by technical, methodological, regulatory, and societal challenges. Drawing on the experiences of six Horizon Europe projects in the MetReal cluster, this review summarizes common barriers and emerging solutions for the use of real‐world data in regulatory decision‐making. Key challenges include complex and lengthy data access procedures, fragmented governance frameworks, variable data quality and completeness, limited interoperability, methodological difficulties in analyzing heterogeneous datasets, and infrastructure constraints within secure data environments. The article highlights opportunities to address these barriers through improved metadata, harmonization, federated analytics, synthetic data sandboxes, sustainable funding, and stronger collaboration between researchers, regulators, health technology assessment bodies, data holders, and citizens. These recommendations aim to strengthen Europe's health data ecosystem and support more robust, efficient, and trusted evidence generation for public health and patient benefit.

Background: Parkinson's disease (PD) and sensorineural hearing loss (SNHL) are both prevalent conditions among older adults. Although increasing number of studies have investigated SNHL as a risk factor for PD, it is not well known how diagnosed PD affects the likelihood of SNHL diagnosis. Objectives: To evaluate the temporal changes in the amount of SNHL diagnoses in relation to PD diagnosis. Methods: This nationwide register‐based study included 22,189 community‐dwelling persons who received a clinically verified PD diagnosis in 1996–2015 in Finland and a 1:1 matched comparison cohort. PD diagnoses were identified from the Special Reimbursement Register and SNHL diagnoses were extracted from Care Register for Healthcare. Incidences of the diagnoses were calculated per 100 person‐years (PY) for each six‐month period from ten years before to ten years after PD diagnosis. Results: Before PD diagnosis the incidence of SNHL diagnosis was higher among people with PD (0.65/100 PY) than in the comparison cohort (0.58/100 PY, hazard ratio, 95% CI 1.11, 1.05–1.18) and increased similarly in both groups. After PD diagnosis the incidence was lower among people with PD (1.00 and 1.28/100 PY, hazard ratio, 95% Cl 0.78, 0.74–0.83) and declined shortly after PD diagnosis whereas it continued to increase in the comparison group. Conclusions: After PD diagnosis, the incidence of SNHL appears to decline compared to the control group, suggesting a possible deprioritization of hearing care. Our findings are also consistent with previous research showing an association between SNHL and PD, with a higher incidence of SNHL observed in individuals with PD.

BACKGROUND Target trial emulation (TTE) studies are increasingly important for regulatory decision‑making and health technology assessments (HTAs), but current risk-of-bias (RoB) tools are not specifically tailored to assess biases central to TTE studies—such as immortal time bias, misaligned eligibility criteria, and prevalent user bias. RoB assessment for TTE studies thus remains difficult, and it is unclear which tools and adaptations researchers currently use or how well they work. OBJECTIVE This study aims to analyze the RoB assessment of TTE studies at regulatory and policy decision points along the medical product life cycle by providing a systematic overview of tools developed, used, adapted, or evaluated for TTE studies and the perceived importance and feasibility of assessing TTE studies by HTA assessors, regulators, systematic reviewers, and methods experts. METHODS This is a protocol for a scoping review and online survey among systematic reviewers, methods experts, European HTA organizations, and regulators. We will collect data on the name, description, and feasibility of RoB tools used, adapted, and developed for TTE studies, as well as RoB assessment results and the RoB sources relevant for TTE studies. Two authors will use qualitative content analysis to analyze the data independently. The systematic search for published and gray literature in 4 electronic databases (PubMed, Scopus, Web of Science, and the Cochrane Library), on relevant websites (eg, Cochrane, HTA and regulatory agencies), and through reference list checking was conducted in May to June 2026. RESULTS As of August 25, 2026, screening is ongoing, and 78 references have been preliminarily included in the scoping review. We will analyze the scoping review and survey data and provide an overview of the types, feasibility, and assessment results of RoB tools currently used, adapted, or developed for TTE studies, as well as the RoB sources considered relevant for TTE studies by HTA assessors, regulators, systematic reviewers, and methods experts. Analysis results of the literature review and survey are expected in September 2026 and November 2026, respectively. CONCLUSIONS The analysis of the scoping review and survey data will inform users of TTE evidence about the feasibility of RoB tools; future development and training needs; and the perceived value of assessing the RoB in HTAs, regulatory decisions, and systematic reviews. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/107499

Background: Psychotropic use and psychotropic polypharmacy are common in people with intellectual disabilities, but representative population‐based studies on this topic are scarce. We evaluated the prevalence of psychotropic use and psychotropic polypharmacy in a Finnish nationwide cohort of people with intellectual disabilities aged 0–97 years. Methods: The annual prevalence of psychotropic use in 2019 was studied among 37 196 individuals with intellectual disabilities and an age‐ and sex‐matched comparison cohort with no diagnosis of intellectual disabilities. Psychotropics included antipsychotics, antidepressants, anxiolytics, hypnotics and sedatives and antiepileptics indicated for bipolar disorder (carbamazepine, valproic acid, lamotrigine, pregabalin and clonazepam). Prevalence of interclass psychotropic polypharmacy (use from ≥ 2 different psychotropic groups) was evaluated in a 4‐month time window at the end of 2019. Results: Prevalence of psychotropic use was higher in the intellectual disability cohort (42.3%) than comparison cohort (15.0%). Antipsychotics were the most common psychotropic group in the intellectual disability cohort (28%), with lower prevalence in the comparison cohort (3.3%). The prevalence of antidepressant use was 19.4% in the intellectual disability cohort and 9.7% in the comparison cohort. A likely indication was identified for 52.9% of psychotropic users with intellectual disability (major psychiatric comorbidity 38.1%, challenging behaviour 22.1%). Psychotropic polypharmacy was more common in the intellectual disability cohort (18.2%), than in the comparison cohort (3.6%). Conclusions: Our findings highlight concerns about psychotropic polypharmacy and potential overmedication. Using a comprehensive, nationwide cohort, this study emphasises the need for more evidence‐based, person‐centred approaches, including careful diagnostics, non‐pharmacological interventions and regular treatment reviews.

Purpose: Prevalence of breast cancer (BC) increases with age, but the external validity of data obtained from pivotal trials of medicinal products remains a concern due to the underrepresentation of frail and older adults. Cyclin‐dependent kinase inhibitors (CDKi), palbociclib, abemaciclib, and ribociclib are considered an essential part of the standard‐of‐care in the management of advanced/metastatic breast cancer. We investigated age, comorbidities, and survival in a nationwide real‐world cohort of CDKi users. Methods: Data from the Finnish Cancer Registry, reimbursed dispensed prescriptions, Electronic Prescription Database, Care Register for Health Care (CRHC), and Causes of Death Register were combined and analysed. Results: Altogether 1921 women with BC initiated CDKi treatment in 2018–2022. The median age at initiation was 66.9 years, with 43.2% of the study cohort being < 65 years of age, 36.1% 65–74 years, 19.0% 75–84 years, and 1.7% 85 years or older. The prevalence of age or frailty‐related comorbidities in individuals ≥ 65 years was low, highest for cardiovascular diseases, 32.3%, and diabetes, 16.9%. The median survival was 25.3 months, with longer median survival times in younger age groups (27.7 months in < 65 year‐olds, 25.1 months in aged 65–74, 21.4 months in aged 75–84 years, and 15.4 months in 85 years or older). Conclusions: Real‐world CDKi users are older than women included in the pivotal trials, and the survival differences between age groups imply challenges in the generalisability of data from pivotal trials. The real‐world CDKi user population is characterised by a low prevalence of major comorbidities.

A French signal detection study identified an association between sulfonamide diuretics use, particularly furosemide, and lower Parkinson's disease (PD) risk. Our aim was to confirm this association in a Finnish nationwide nested case–control study (FINPARK), primarily in an indication‐restricted case–control study of persons with heart or renal failure. Altogether 19 568 PD cases diagnosed in 1999–2015 and 130 156 age, sex and region‐matched controls were included. The case–control study restricted to those with heart or renal failure included 1222 PD cases and 4766 matched controls. Furosemide use was identified from Prescription Register (1995–2015). The main analysis considered exposure at least 3 years before the matching date (3‐year lag). Additional analyses with no lag, 5‐ and 8‐year lags were conducted. Furosemide was not associated with PD risk (adjusted OR, 95% CI 1.00, 0.87–1.15 for user–non‐user comparison with 3‐year lag). A statistically significant borderline association between higher exposure levels and lower PD risk was observed in comparing risk across categories of cumulative furosemide exposure (adjusted OR, 95% CI 0.80, 0.64–1.00 with 3‐year lag). Our nationwide indication‐restricted case–control study of persons with PD found no robust evidence on the association between furosemide use and PD risk. However, there was suggestive evidence of reduced risk for participants in the highest exposure category.

Purpose: To evaluate the diagnostic validity of PD identification in a national health registry requiring neurologist-confirmed diagnoses. Patients and Methods: We analyzed the Turku PD Cohort including 1626 patients diagnosed with PD between 2006 and 2020 in specialist care. Patients were identified based on ≥ 2 entries of ICD-10 code G20. Diagnoses were re-evaluated through detailed chart review after a median follow-up of approximately 10 years. Two movement disorder specialists independently classified final diagnoses based on clinical records, imaging, and treatment data. Linkage to the Finnish Register of the Entitlements to Reimbursement of Pharmaceutical Expenses identified patients granted reimbursement for antiparkinsonian medications under ICD-10 code G20. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using the final clinical diagnosis as the reference. Results: Of the 1626 patients, 1550 (95.3%) had received reimbursement for PD medications. After long-term follow-up, 1314 were confirmed as PD and 236 reclassified to alternative diagnoses. Registry identification showed high sensitivity (98.2%) and PPV (84.8%). Only 24 confirmed PD cases (1.8%) were not captured. Diagnostic revisions most commonly reflected atypical or secondary parkinsonian syndromes. Specificity was lower (18.1%), reflecting diagnostic evolution during follow-up rather than systematic miscoding. The median delay between diagnosis and registry entry was 24 days. Conclusion: A national health registry requiring neurologist-confirmed diagnoses enables highly sensitive PD case identification with good PPV for epidemiological research. However, diagnostic evolution in early parkinsonism limits specificity in cross-sectional register data. Registry studies should therefore apply follow-up exclusion algorithms for alternative parkinsonian diagnoses.