Analyzing change in medication use - statistical approaches

The objective of this study was to gain an understanding of the effects of population heterogeneity, missing data, and causal relationships on parameter estimates from statistical models when analyzing change in medication use. From a public health perspective, two timely topics were addressed: the use and effects of statins in populations in primary prevention of cardiovascular disease and polypharmacy in older population. Growth mixture models were applied to characterize the accumulation of cardiovascular and diabetes medications among apparently healthy population of statin initiators. The causal effect of statin adherence on the incidence of acute cardiovascular events was estimated using marginal structural models in comparison with discrete-time hazards models. The impact of missing data on the growth estimates of evolution of polypharmacy was examined comparing statistical models under different assumptions for missing data mechanism. The data came from Finnish administrative registers and from the population-based Geriatric Multidisciplinary Strategy for the Good Care of the Elderly study conducted in Kuopio, Finland, during 2004–07. Five distinct patterns of accumulating medications emerged among the population of apparently healthy statin initiators during two years after statin initiation. Proper accounting for time-varying dependencies between adherence to statins and confounders using marginal structural models produced comparable estimation results with those from a discrete-time hazards model. Missing data mechanism was shown to be a key component when estimating the evolution of polypharmacy among older persons. In conclusion, population heterogeneity, missing data and causal relationships are important aspects in longitudinal studies that associate with the study question and should be critically assessed when performing statistical analyses. Analyses should be supplemented with sensitivity analyses towards model assumptions.Lääkkeen käytön muutoksen analysointi – tilastollisia näkökulmia. Väitöskirjatutkimuksen tavoitteena oli lisätä ymmärrystä populaation heterogeenisyyden, puuttuvan tiedon sekä kausaalisuhteiden vaikutuksesta tilastollisten mallien parametrien estimaatteihin analysoitaessa lääkkeiden käytön muutosta. Tutkimus keskittyi kahteen kansanterveyden näkökulmasta ajankohtaiseen aiheeseen: statiinien käyttöön ja vaikutuksiin sydän- ja verisuonisairauksien primaaripreventiossa sekä iäkkäiden monilääkitykseen. Sydän- ja verisuonisairaus- sekä diabeteslääkkeiden kertymistä kuvailtiin näennäisesti terveillä statiinihoidon aloittajilla latentin kasvukäyrämallin mixture-analyysin avulla. Statiinihoitoon sitoutumisen kausaalivaikutusta akuuttiin sydän- ja verisuonitapahtumaan primaaripreventiossa estimoitiin marginaalisilla rakennemalleilla ja verrattiin diskreetin elinaikamallin tuloksiin. Puuttuvan tiedon vaikutusta kasvufaktoreiden estimaatteihin monilääkityksen kehitystä analysoitaessa tutkittiin vertailemalla tilastollisia menetelmiä jotka erosivat toisistaan oletuksiltaan puuttuvan tiedon mekanismista. Aineistoina käytettiin suomalaisia hallinnollisia rekistereitä sekä Kuopiossa vuosina 2004–07 toteutetun Hyvän Hoidon Strategia-tutkimuksen aineistoa. Näennäisesti terveillä statiinihoidon aloittajilla havaittiin viisi toisistaan erillistä lääkkeiden kertymisen kehityskaarta kahden vuoden aikana statiinin aloituksesta. Kun marginaalisen rakennemallin avulla huomioitiin statiinihoitoon sitoutumisen ja sekoittavien tekijöiden muutokset, joihin aiempi hoitoon sitoutuminen saattoi vaikuttaa, tuloksena oli diskreetin elinaikamallin kanssa yhteneviä parametriestimaatteja. Puuttuvan tiedon mekanismi osoittautui avaintekijäksi estimoitaessa monilääkityksen kehitystä iäkkäässä väestössä. Yhteenvetona todetaan, että lääkkeiden käytön muutoksen tilastollisissa analyyseissä on tärkeää ottaa huomioon populaation heterogeenisyys, puuttuvan tiedon mekanismi ja muuttujien väliset kausaalisuhteet. Sovellettavan tilastollisen menetelmän tulisi vastata tutkimuskysymystä ja analyysien tuloksia tulisi tukea herkkyysanalyyseillä tilastollisten mallien oletuksia kohtaan.Siirretty Doriast

Short-term impact of co-payment level increase on the use of medication and patient-reported outcomes in Finnish patients with type 2 diabetes

A new reimbursement scheme for non-insulin medications used for treatment of hyperglycemia in type 2 diabetes (T2D) was implemented in Finland on January 1, 2017. The aim of the study was to evaluate the impact of this co-payment increase (i.e. + 35 percentage points) on patient-reported satisfaction for diabetes care, diabetes medication use, and financial difficulties. Baseline data were collected in 114 pharmacies, where patients with T2D were asked to fill in a questionnaire in November 2016. Follow-ups were conducted at 6 and 12 months. In total, 955 participants with T2D attended the baseline examination. During the follow-up, satisfaction with diabetes care decreased significantly (p <0.001). Use of insulin increased (OR 1.16, 95 % CI 1.06-1.27) whereas use of metformin and DPP-4 inhibitors decreased (metformin: OR 0.80,95 % CI 0.70-0.90; DPP-4 inhibitors: OR 0.82, 95 % CI 0.73-0.93). Financial difficulties with the purchase of diabetes medications were reported more often both at 6 (OR 2.44,95 % CI 1.96-3.03) and at 12 months (OR 2.70, 95 % CI 2.18-3.35) than at baseline. These negative short-term effects require future studies. If persistent, the long-term effects of lower treatment satisfaction and increased financial difficulties may imply impaired metabolic control and increased diabetes complication risk and health care costs. Patient perspective should be taken into account in future policy making. (C) 2020 The Author(s). Published by Elsevier B.V.Peer reviewe

Accumulation of Cardiovascular and Diabetes Medication among Apparently Healthy Statin Initiators

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Risk of head and traumatic brain injuries associated with antidepressant use among community-dwelling persons with Alzheimer’s disease : a nationwide matched cohort study

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Impact of type 2 diabetes treated with non-insulin medication and number of diabetes-coexisting diseases on EQ-5D-5L index scores in the Finnish population

Background: Type 2 diabetes (T2D) causes significant health and economic burden. In addition to comorbidities there are also coexisting diseases linked to obesity, lifestyle and T2D. The aim of this study was to examine the effect of T2D and T2D-coexisting diseases on health-related quality of life (HRQoL) in the Finnish population and whether it is T2D or the coexisting diseases that have the largest impact on HRQoL.Methods: The study was based on a national cross-sectional population survey (n=5305). Respondents' HRQoL was measured using the EQ-5D-5L instrument. Our study included diabetic respondents treated with non-insulin medications (NI-T2D) with or without insulin and non-diabetic respondents, whereas diabetic respondents not taking any anti-diabetic medications or treated with insulin alone were excluded. A crosswalk algorithm was used to convert EQ-5D-5L index scores into EQ-5D-3L index scores as a sensitivity analysis. A two-part model was used to examine the association between T2D and coexisting diseases and HRQoL.Results: The unadjusted mean (SD) EQ-5D-5L index scores for non-diabetics (n=4856) was 0.90 (0.13) and 0.85 (0.16) for respondents with NI-T2D (n=449). With adjustment for demographic factors, the difference in EQ-5D-5L index scores was 0.036 (95% CI 0.023-0.050). After adjusting for the number of coexisting diseases, the EQ-5D-5L index scores among respondents with NI-T2D and three or more coexisting diseases were lower when compared to all non-diabetics but not when compared to non-diabetics with similar number of coexisting diseases. The number of T2D-coexisting diseases had a larger effect on EQ-5D-5L index scores in younger age groups (20 and 40years old).Conclusions: Lower EQ-5D-5L index score is associated with NI-T2D when compared to non-diabetic respondents. When compared to non-diabetics, the disutility associated with NI-T2D increases as more coexisting diseases appear. The disutility effect of coexisting diseases was equally large in non-diabetics and respondents with NI-T2D. Thus, public health interventions targeting the prevention of both T2D and its coexisting diseases have potential to have significant benefits also in terms of HRQoL.</p

Economic evaluation of using polygenic risk score to guide risk screening and interventions for the prevention of type 2 diabetes in individuals with high overall baseline risk

Type 2 diabetes (T2D) with increasing prevalence is a significant global public health challenge. Obesity, unhealthy diet, and low physical activity are one of the major determinants of the rise in T2D prevalence. In addition, family history and genetic risk of diabetes also play a role in the process of developing T2D. Therefore, solutions for the early identification of individuals at high risk for T2D for early targeted detection of T2D, prevention, and intervention are highly preferred. Recently, novel genomic-based polygenic risk scores (PRSs) have been suggested to improve the accuracy of risk prediction supporting the targeting of preventive interventions to those at highest risk for T2D. Therefore, the aim of the present study was to assess the cost-utility of an additional PRS testing information (as a part of overall risk assessment) followed by a lifestyle intervention and an additional medical therapy when estimated 10-year overall risk for T2D exceeded 20% among Finnish individuals screened as at the high-risk category (i.e., 10%-20% 10-year overall risk of T2D) based on traditional risk factors only. For a cost-utility analysis, an individual-level state-transition model with probabilistic sensitivity analysis was constructed. A 1-year cycle length and a lifetime time horizon were applied in the base-case. A 3% discount rate was used for costs and QALYs. Cost-effectiveness acceptability curve (CEAC) and estimates for the expected value of perfect information (EVPI) were calculated to assist decision makers. The use of the targeted PRS strategy reclassified 12.4 percentage points of individuals to be very high-risk individuals who would have been originally classified as high risk using the usual strategy only. Over a lifetime horizon, the targeted PRS was a dominant strategy (i.e., less costly, more effective). One-way and scenario sensitivity analyses showed that results remained dominant in almost all simulations. However, there is uncertainty, since the probability (EVPI) of cost-effectiveness at a WTP of 0(sic)/QALY was 63.0% (243(sic)) indicating the probability that the PRS strategy is a dominant option. In conclusion, the results demonstrated that the PRS provides moderate additional value in Finnish population in risk screening leading to potential cost savings and better quality of life when compared with the current screening methods for T2D risk.Peer reviewe

Statin adherence and risk of acute cardiovascular events among women : a cohort study accounting for time-dependent confounding affected by previous adherence

Objectives Previous studies on the effect of statin adherence on cardiovascular events in the primary prevention of cardiovascular disease have adjusted for time-dependent confounding, but potentially introduced bias into their estimates as adherence and confounders were measured simultaneously. We aimed to evaluate the effect when accounting for time-dependent confounding affected by previous adherence as well as time sequence between factors. Design Retrospective cohort study. Setting Finnish healthcare registers. Participants Women aged 45-64years initiating statin use for primary prevention of cardiovascular disease in 2001-2004 (n=42807). Outcomes Acute cardiovascular event defined as a composite of acute coronary syndrome and acute ischaemic stroke was our primary outcome. Low-energy fractures were used as a negative control outcome to evaluate the healthy-adherer effect. Results During the 3-year follow-up, 474 women experienced the primary outcome event and 557 suffered a low-energy fracture. The causal HR estimated with marginal structural model for acute cardiovascular events for all the women who remained adherent (proportion of days covered 80%) to statin therapy during the previous adherence assessment year was 0.78 (95% CI: 0.65 to 0.94) when compared with everybody remaining non-adherent (proportion of days covered Conclusions Our study, which took into account the time dependence of adherence and confounders, as well as temporal order between these factors, is support for the concept that adherence to statins in women in primary prevention decreases the risk of acute cardiovascular events by about one-fifth in comparison to non-adherence. However, part of the observed effect of statin adherence on acute cardiovascular events may be due to the healthy-adherer effect.Peer reviewe

Kulttuurihyvinvointitoiminnan taloudellinen arviointi : Arviointimenetelmien jatkokehitystarpeet Suomessa

Hankkeen tavoitteena oli 1) kehittää kulttuurihyvinvointitoimien ennakoivassa taloudellisessa arvioinnissa tarvittavia menetelmiä ja laskentamalleja, 2) kehittää arvioinnin kriteeristöjä, 3) tunnistaa arviointia tukevan tietotuotannon tarpeita sekä 4) tehdä näiden pohjalta toimenpidesuosituksia kulttuurihyvinvointitoimien taloudellisen arvioinnin kehittämiseksi Suomessa. Hankkeessa tunnistettiin sidosryhmähaastatteluiden avulla kulttuurihyvinvointitoiminnan taloudellisen arvioinnin mahdollisuuksia ja haasteita Suomessa sekä kartoitettiin kirjallisuuskatsauksella kulttuurihyvinvointitoiminnan vaikuttavuustutkimuksen nykytilaa kansainvälisesti. Lisäksi hankkeessa pilotoitiin kirjallisuudesta tunnistettuja koetun hyvinvoinnin mittareita kulttuurihyvinvointitoiminnan vaikuttavuuden arvioinnissa. Viimeisessä osahankkeessa sovellettiin terveystaloudellisen mallinnuksen menetelmiä esimerkinomaisesti osallisuutta tukevan kulttuurihyvinvointitoiminnan taloudellisessa arvioinnissa. Tällä hetkellä kulttuurihyvinvointitoiminnan vaikuttavuustutkimus on sekä kansallisesti että kansainvälisesti tarkastellen vähäistä ja pistemäistä. Alan toimijat ja organisaatiot ovat kuitenkin valmiita vaikuttavuusperustaiseen yhteistyöhön. Tämä edellyttää kuitenkin konkreettisia tekoja ja tarvittavan tietopohjan rakentamista, mikä vahvistaa kulttuurihyvinvointitoiminnan vaikuttavuuden arviointia ja mittaamista.Tämä julkaisu on toteutettu osana valtioneuvoston selvitys- ja tutkimussuunnitelman toimeenpanoa. (tietokayttoon.fi) Julkaisun sisällöstä vastaavat tiedon tuottajat, eikä tekstisisältö välttämättä edusta valtioneuvoston näkemystä

Digitally Supported Lifestyle Intervention to Prevent Type 2 Diabetes Through Healthy Habits : Secondary Analysis of Long-Term User Engagement Trajectories in a Randomized Controlled Trial

Background: Digital health interventions may offer a scalable way to prevent type 2 diabetes (T2D) with minimal burden on health care systems by providing early support for healthy behaviors among adults at increased risk for T2D. However, ensuring continued engagement with digital solutions is a challenge impacting the expected effectiveness. Objective: We aimed to investigate the longitudinal usage patterns of a digital healthy habit formation intervention, BitHabit, and the associations with changes in T2D risk factors. Methods: This is a secondary analysis of the StopDia (Stop Diabetes) study, an unblinded parallel 1-year randomized controlled trial evaluating the effectiveness of the BitHabit app alone or together with face-to-face group coaching in comparison with routine care in Finland in 2017-2019 among community-dwelling adults (aged 18 to 74 years) at an increased risk of T2D. We used longitudinal data on usage from 1926 participants randomized to the digital intervention arms. Latent class growth models were applied to identify user engagement trajectories with the app during the study. Predictors for trajectory membership were examined with multinomial logistic regression models. Analysis of covariance was used to investigate the association between trajectories and 12-month changes in T2D risk factors. Results: More than half (1022/1926, 53.1%) of the participants continued to use the app throughout the 12-month intervention. The following 4 user engagement trajectories were identified: Terminated usage (904/1926, 46.9%), weekly usage (731/1926, 38.0%), twice weekly usage (208/1926, 10.8%), and daily usage (83/1926, 4.3%). Active app use during the first month, higher net promoter score after the first 1 to 2 months of use, older age, and better quality of diet at baseline increased the odds of belonging to the continued usage trajectories. Compared with other trajectories, daily usage was associated with a higher increase in diet quality and a more pronounced decrease in BMI and waist circumference at 12 months. Conclusions: Distinct long-term usage trajectories of the BitHabit app were identified, and individual predictors for belonging to different trajectory groups were found. These findings highlight the need for being able to identify individuals likely to disengage from interventions early on, and could be used to inform the development of future adaptive interventions.publishedVersionPeer reviewe