Lag time to benefit for preventive therapies

Better guidelines for better care: accounting for multimorbidity in clinical guidelines – structured examination of exemplar guidelines and health economic modelling

Background

Multimorbidity is common but most clinical guidelines focus on single diseases.

Aim

To test the feasibility of new approaches to developing single-disease guidelines to better account for multimorbidity.

Design

Literature-based and economic modelling project focused on areas where multimorbidity makes guideline application problematic.

Methods

(1) Examination of accounting for multimorbidity in three exemplar National Institute for Health and Care Excellence guidelines (type 2 diabetes, depression, heart failure); (2) examination of the applicability of evidence in multimorbidity for the exemplar conditions; (3) exploration of methods for comparing absolute benefit of treatment; (4) incorporation of treatment pay-off time and competing risk of death in an exemplar economic model for long-term preventative treatments with slowly accruing benefit; and (5) development of a discrete event simulation model-based cost-effectiveness analysis for people with both depression and coronary heart disease.

Results

(1) Comorbidity was rarely accounted for in the clinical research questions that framed the development of the exemplar guidelines, and was rarely accounted for in treatment recommendations. Drug–disease interactions were common only for comorbid chronic kidney disease, but potentially serious drug–drug interactions between recommended drugs were common and rarely accounted for in guidelines. (2) For all three conditions, the trials underpinning treatment recommendations largely excluded older, more comorbid and more coprescribed patients. The implications of low applicability varied by condition, with type 2 diabetes having large differences in comorbidity, whereas potentially serious drug–drug interactions were more important for depression. (3) Comparing absolute benefit of treatments for different conditions was shown to be technically feasible, but only if guideline developers are willing to make a number of significant assumptions. (4) The lifetime absolute benefit of statins for primary prevention is highly sensitive to the presence of both the direct treatment disutility of taking a daily tablet and competing risk of death. (5) It was feasible to use a discrete event simulation-based model to represent the relevant care pathways to estimate the relative cost-effectiveness of pharmacological treatments of major depressive disorder in primary care for patients who are also likely to go on and receive treatment for coronary heart disease but the analysis was reliant on eliciting some parameter values from experts, which increases the inherent uncertainty in the results. The key limitation was that real-life use in guideline development was not examined.

Conclusions

Guideline developers could feasibly (1) use epidemiological data characterising the guideline population to inform consideration of applicability and interactions; (2) systematically compare the absolute benefit of long-term preventative treatments to inform decision-making in people with multimorbidity and high treatment burden; and (3) modify the output from economic models used in guideline development to examine time to benefit in terms of the pay-off time and varying competing risk of death from other conditions.

Future work

Further research is needed to optimise presentation of comparative absolute benefit information to clinicians and patients, to evaluate the use of epidemiological and time-to-benefit data in guideline development, to better quantify direct treatment disutility and to better quantify benefit and harm in people with multimorbidity.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Advanced Age and Medication Prescription: More Years, Less Medications? A Nationwide Report From the Italian Medicines Agency

BACKGROUND

In older adults co-occurrence of multiple diseases often leads to use of multiple medications (polypharmacy). The aim of the present study is to describe how prescription of medications varies across age groups, with specific focus on the oldest old.

METHODS

We performed a cross-sectional study using 2013 data from the OsMed Health-DB database (mean number of medicines and defined daily doses prescribed in 15,931,642 individuals). There were 3,378,725 individuals age 65 years or older (21.2% of the study sample).

RESULTS

The mean number of prescribed medications progressively rose from 1.9 in the age group <65 years to 7.4 in the age group 80-84 years and then declined, with a more marked reduction in the age group 95 years or older with a mean number of 2.8 medications. A similar pattern was observed for the mean number of defined daily doses. Among participants age ≥65 years, proton pump inhibitors were the most commonly prescribed medication (40.9% of individuals ≥65 years), followed by platelet aggregation inhibitors (32.8%) and hydroxy-methylglutaryl-coenzyme A reductase inhibitors (26.1%). A decline in prescription was observed among individuals age 90 years or older, but this reduction was less consistent for medications used to treat acute conditions (ie, antibiotics and glucocorticoids) rather than preventive medicines commonly used to treat chronic diseases (ie, antihypertensive medications and hydroxy-methylglutaryl-coenzyme A reductase inhibitors).

CONCLUSIONS

The burden of medication treatment progressively increases till age 85 and substantially declines after age of 90 years. Patterns of medication prescription widely vary across age groups.