Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study

Spreafico, Marta; Gasperoni, Francesca; Barbati, Giulia; Ieva, Francesca; Scagnetto, Arjuna; Zanier, Loris; Iorio, Annamaria; Sinagra, Gianfranco; Lenarda, Andrea Di

doi:10.1007/s40256-019-00367-z

Cited by 13 publications

(11 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In patients with HF, high medication burden could lead to poor medication adherence and persistence, 7 drug-drug interactions, 8 underuse of effective treatment, inappropriate drug prescription, adverse drug-related effects, 9 and multiple taste disturbances. 26 …”

Section: Discussionmentioning

confidence: 99%

“…Apart from comorbidities, this study found that DBP <80 mmHg was likely an underlying predictor of super hyperpolypharmacy in patients with HFpEF, which was consistent with the findings of previous studies suggesting that a low DBP elevated the risks of adverse outcomes in patients with HFpEF, 24 and that the relationship between decreasing DBP and increased risk of hospitalisation was linear. 25 In patients with HF, high medication burden could lead to poor medication adherence and persistence, 7 drugdrug interactions, 8 underuse of effective treatment, inappropriate drug prescription, adverse drug-related effects, 9 and multiple taste disturbances. 26 High medication burden is common among older people with multiple comorbidities who usually have poorer medication compliance than young patients.…”

Section: Comparison With Existing Literaturementioning

confidence: 99%

“…Current therapeutic regimens could lead to a heavy medication burden such as polypharmacy 3 and hyperpolypharmacy. 4 In patients with HF, a previous review 3 has revealed that polypharmacy was an underacknowledged cause of health problems, 5 , 6 and it also elucidated a detrimental impact of polypharmacy on medication compliance, 7 drug-drug interactions, 8 incidence of underprescription and inaccurate prescription, and drug-related adverse reactions. 9 The most common type of HF is HF with preserved ejection fraction (HFpEF), which will have an increasing prevalence in the upcoming decades.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Influence of polypharmacy on patients with heart failure with preserved ejection fraction: a retrospective analysis on adverse outcomes in the TOPCAT trial

Zhu

et al. 2020

Br J Gen Pract

View full text Add to dashboard Cite

BackgroundPolypharmacy is common in heart failure (HF), whereas its effect on adverse outcomes in patients with HF with preserved ejection fraction (HFpEF) is unclear.AimTo evaluate the prevalence, prognostic impacts, and predictors of polypharmacy in HFpEF patients.Design and settingA retrospective analysis performed on patients in the Americas region (including the US, Canada, Argentina, and Brazil) with symptomatic HF and a left ventricular ejection fraction ≥45% in the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist) trial, an international, randomised, double-blind, placebo-controlled study conducted during 2006–2013 in six countries.MethodPatients were categorised into four groups: controls (<5 medications), polypharmacy (5–9 medications), hyperpolypharmacy, (10– 14 medications), and super hyperpolypharmacy (≥15 medications). The outcomes and predictors in all groups were assessed.ResultsOf 1761 participants, the median age was 72 years; 37.5% were polypharmacy, 35.9% were hyperpolypharmacy, and 19.6% were super hyperpolypharmacy, leaving 7.0% having a low medication burden. In multivariable regression models, three experimental groups with a high medication burden were all associated with a reduction in all-cause death, but increased risks of HF hospitalisation and all-cause hospitalisation. Furthermore, several comorbidities (dyslipidemia, thyroid diseases, diabetes mellitus, and chronic obstructive pulmonary disease), a history of angina pectoris, diastolic blood pressure <80 mmHg, and worse heart function (the New York Heart Association functional classification level III and IV) at baseline were independently associated with a high medication burden among patients with HFpEF.ConclusionA high prevalence of high medication burden at baseline was reported in patients with HFpEF. The high medication burden might increase the risk of hospital readmission, but not the mortality.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Comparison With Existing Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Influence of polypharmacy on patients with heart failure with preserved ejection fraction: a retrospective analysis on adverse outcomes in the TOPCAT trial

Zhu

et al. 2020

Br J Gen Pract

View full text Add to dashboard Cite

show abstract

“…In fact, in the administrative database the number of days of treatment covered by the prescription was based on the number of boxes and the DDD. The use of theoretical DDD instead of prescribed daily doses (PDD) could reflect a bias in the estimated adherence if the underlying PDD/DDD ratio is different from 1 (Grimmsmann & Himmel, 2011; Spreafico et al., 2020; World Health Organization, 2003b). Therefore, it could be interesting to explore, whenever the linkage is possible, databases with information about dosages prescribed by doctors, in order to obtain a more realistic analysis of coverage periods.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, we assumed full adherence during rehospitalization period (Andrade et al., 2006), and we based our analysis on purchased drugs instead of prescribed drugs, as done in Spreafico et al. (2020). In particular, for each month, we first computed the cumulative coverage days up to the current month

t

.…”

Section: Data Setmentioning

confidence: 99%

Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time‐varying covariates

Spreafico

Ieva

2020

Biometrical J

Self Cite

View full text Add to dashboard Cite

Adherence to medication is the process by which patients take their drugs as prescribed, and represents an issue in pharmacoepidemiological studies. Poor adherence is often associated with adverse health conditions and outcomes, especially in case of chronic diseases such as heart failure (HF). This turns out in an increased request for health care services, and in a greater burden for the health care system. In recent years, there has been a substantial growth in pharmacotherapy research, aimed at studying effects and consequences of proper/improper adherence to medication both for the increasing awareness of the problem and for the pervasiveness of poor adherence among patients. However, the way adherence is computed and accounted for into predictive models is far from being informative as it may be. In fact, it is usually analyzed as a fixed baseline covariate, without considering its time‐varying behavior. The purpose and novelty of this study is to define a new personalized monitoring tool exploiting time‐varying definition of adherence to medication, within a joint modeling approach. In doing so, we are able to capture and quantify the association between the longitudinal process of dynamic adherence to medication with the long‐term survival outcome. Another novelty of this approach consists of exploiting the potential of health care administrative databases in order to reconstruct the dynamics of drugs consumption through pharmaceutical administrative registries. In particular, we analyzed administrative data provided by Regione Lombardia ‐ Healthcare Division related to patients hospitalized for HF between 2000 and 2012.

show abstract

Functional modeling of recurrent events on time‐to‐event processes

Spreafico

Ieva

2021

Biometrical J

Self Cite

View full text Add to dashboard Cite

In clinical practice, it is often the case where the association between the occurrence of events and time‐to‐event outcomes is of interest; thus, it can be modeled within the framework of recurrent events. The purpose of our study is to enrich the information available for modeling survival with relevant dynamic features, properly taking into account their possibly time‐varying nature, as well as to provide a new setting for quantifying the association between time‐varying processes and time‐to‐event outcomes. We propose an innovative methodology to model information carried out by time‐varying processes by means of functional data, modeling each time‐varying variable as the compensator of marked point process the recurrent events are supposed to derive from. By means of Functional Principal Component Analysis, a suitable dimensional reduction of these objects is carried out in order to plug them into a Cox‐type functional regression model for overall survival. We applied our methodology to data retrieved from the administrative databases of Lombardy Region (Italy), related to patients hospitalized for Heart Failure (HF) between 2000 and 2012. We focused on time‐varying processes of HF hospitalizations and multiple drugs consumption and we studied how they influence patients' overall survival. This novel way to account for time‐varying variables allowed to model self‐exciting behaviors, for which the occurrence of events in the past increases the probability of a new event, and to quantify the effect of personal behaviors and therapeutic patterns on survival, giving new insights into the direction of personalized treatment.

show abstract

Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study

Cited by 13 publications

References 22 publications

Influence of polypharmacy on patients with heart failure with preserved ejection fraction: a retrospective analysis on adverse outcomes in the TOPCAT trial

Influence of polypharmacy on patients with heart failure with preserved ejection fraction: a retrospective analysis on adverse outcomes in the TOPCAT trial

Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time‐varying covariates

Functional modeling of recurrent events on time‐to‐event processes

Contact Info

Product

Resources

About