Guidance on the use of complex systems models for economic evaluations of public health interventions

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

BMI trajectories, morbidity, and mortality in England: a two-step approach to estimating consequences of changes in BMI

OBJECTIVE

BMI is known to have an association with morbidities and mortality. Many studies have argued that identifying health risks using single BMI measures has limitations, particularly in older adults, and that changes in BMI can help to identify risks. This study identifies distinct BMI trajectories and their association with the risks of a range of morbidities and mortality.

METHODS

The English Longitudinal Study of Aging provides data on BMI, mortality, and morbidities between 1998 and 2015, sampled from adults over 50 years of age. This study uses a growth-mixture model and discrete-time survival analysis, combined using a two-step approach, which is novel in this setting, to the authors' knowledge.

RESULTS

This study identified four trajectories: "stable overweight," "elevated BMI," "increasing BMI," and "decreasing BMI." No differences in mortality, cancer, or stroke risk were found between these trajectories. BMI trajectories were significantly associated with the risks of diabetes, asthma, arthritis, and heart problems.

CONCLUSIONS

These results emphasize the importance of looking at change in BMI alongside most recent BMI; BMI trajectories should be considered where possible when assessing health risks. The results suggest that established BMI thresholds should not be used in isolation to identify health risks, particularly in older adults.

Development of a Web-Based, Guided Self-help, Acceptance and Commitment Therapy-Based Intervention for Weight Loss Maintenance: Evidence-, Theory-, and Person-Based Approach

Background

The long-term impact and cost-effectiveness of weight management programs depend on posttreatment weight maintenance. There is growing evidence that interventions based on third-wave cognitive behavioral therapy, particularly acceptance and commitment therapy (ACT), could improve long-term weight management; however, these interventions are typically delivered face-to-face by psychologists, which limits the scalability of these types of intervention.

Objective

The aim of this study is to use an evidence-, theory-, and person-based approach to develop an ACT-based intervention for weight loss maintenance that uses digital technology and nonspecialist guidance to minimize the resources needed for delivery at scale.

Methods

Intervention development was guided by the Medical Research Council framework for the development of complex interventions in health care, Intervention Mapping Protocol, and a person-based approach for enhancing the acceptability and feasibility of interventions. Work was conducted in two phases: phase 1 consisted of collating and analyzing existing and new primary evidence and phase 2 consisted of theoretical modeling and intervention development. Phase 1 included a synthesis of existing evidence on weight loss maintenance from previous research, a systematic review and network meta-analysis of third-wave cognitive behavioral therapy interventions for weight management, a qualitative interview study of experiences of weight loss maintenance, and the modeling of a justifiable cost for a weight loss maintenance program. Phase 2 included the iterative development of guiding principles, a logic model, and the intervention design and content. Target user and stakeholder panels were established to inform each phase of development, and user testing of successive iterations of the prototype intervention was conducted.

Results

This process resulted in a guided self-help ACT-based intervention called SWiM (Supporting Weight Management). SWiM is a 4-month program consisting of weekly web-based sessions for 13 consecutive weeks followed by a 4-week break for participants to reflect and practice their new skills and a final session at week 18. Each session consists of psychoeducational content, reflective exercises, and behavioral experiments. SWiM includes specific sessions on key determinants of weight loss maintenance, including developing skills to manage high-risk situations for lapses, creating new helpful habits, breaking old unhelpful habits, and learning to manage interpersonal relationships and their impact on weight management. A trained, nonspecialist coach provides guidance for the participants through the program with 4 scheduled 30-minute telephone calls and 3 further optional calls.

Conclusions

This comprehensive approach facilitated the development of an intervention that is based on scientific theory and evidence for supporting people with weight loss maintenance and is grounded in the experiences of the target users and the context in which it is intended to be delivered. The intervention will be refined based on the findings of a planned pilot randomized controlled trial.

The impact of Type 2 diabetes prevention programmes based on risk-identification and lifestyle intervention intensity strategies: a cost-effectiveness analysis

AIMS

To develop a cost-effectiveness model to compare Type 2 diabetes prevention programmes targeting different at-risk population subgroups with a lifestyle intervention of varying intensity.

METHODS

An individual patient simulation model was constructed to simulate the development of diabetes in a representative sample of adults without diabetes from the UK population. The model incorporates trajectories for HbA1c , 2-h glucose, fasting plasma glucose, BMI, systolic blood pressure, total cholesterol and HDL cholesterol. Patients can be diagnosed with diabetes, cardiovascular disease, microvascular complications of diabetes, cancer, osteoarthritis and depression, or can die. The model collects costs and utilities over a lifetime horizon. The perspective is the UK National Health Service and personal social services. We used the model to evaluate the population-wide impact of targeting a lifestyle intervention of varying intensity to six population subgroups defined as high risk for diabetes.

RESULTS

The intervention produces 0.0003 to 0.0009 incremental quality-adjusted life years and saves up to £1.04 per person in the general population, depending upon the subgroup targeted. Cost-effectiveness increases with intervention intensity. The most cost-effective options are to target individuals with HbA1c > 42 mmol/mol (6%) or with a high Finnish Diabetes Risk (FINDRISC) probability score (> 0.1).

CONCLUSION

The model indicates that diabetes prevention interventions are likely to be cost-effective and may be cost-saving over a lifetime. In the model, the criteria for selecting at-risk individuals differentially impact upon diabetes and cardiovascular disease outcomes, and on the timing of benefits. These findings have implications for deciding who should be targeted for diabetes prevention interventions.

Sipuleucel-T for the Treatment of Metastatic Hormone-Relapsed Prostate Cancer: A NICE Single Technology Appraisal; An Evidence Review Group Perspective

The National Institute for Health and Care Excellence (NICE) invited Dendreon, the company manufacturing sipuleucel-T, to submit evidence for the clinical and cost effectiveness of sipuleucel-T for asymptomatic or minimally symptomatic, metastatic, non-visceral hormone-relapsed prostate cancer patients in whom chemotherapy is not yet clinically indicated, as part of NICE's single technology appraisal process. The comparator was abiraterone acetate (AA) or best supportive care (BSC). The School of Health and Related Research at the University of Sheffield was commissioned to act as the Evidence Review Group (ERG). This paper describes the company submission (CS), ERG review, and subsequent decision of the NICE Appraisal Committee (AC). The ERG produced a critical review of the clinical and cost-effectiveness evidence of sipuleucel-T based upon the CS. Clinical-effectiveness data relevant to the decision problem were taken from three randomised controlled trials (RCTs) of sipuleucel-T and a placebo (PBO) comparator of antigen-presenting cells (APC) being re-infused (APC-PBO) (D9901, D9902A and D9902B), and one RCT (COU-AA-302) of AA plus prednisone vs. PBO plus prednisone. Two trials reported a significant advantage for sipuleucel-T in median overall survival compared with APC-PBO: for trial D9901, an adjusted hazard ratio (HR) 0.47; (95 % confidence interval [CI] 0.29, 0.76) p < 0.002; for D9902B, adjusted HR 0.78 (95 % CI 0.61, 0.98) p = 0.03. There was no significant difference between groups in D9902A, unadjusted HR 0.79 (95 % CI 0.48, 1.28) p = 0.331. Sipuleucel-T and APC-PBO groups did not differ significantly in time to disease progression, in any of the three RCTs. Most adverse events developed within 1 day of the infusion, and resolved within 2 days. The CS included an indirect comparison of sipuleucel-T (D9902B) and AA plus prednisone (COU-AA-302). As trials differed in prior use of chemotherapy, an analysis of only chemotherapy-naïve patients was included, in which the overall survival for sipuleucel-T and AA was not significantly different, HR 0.94 (95 % CI 0.69, 1.28) p = 0.699. The ERG had several concerns regarding the data and assumptions incorporated within the company's cost-effectiveness analyses and conducted exploratory analyses to quantify the impact of making alternative assumptions or using alternative data inputs. The deterministic incremental cost-effectiveness ratio (ICER) for sipuleucel-T vs. BSC when using the ERG's preferred data and assumptions was £ 108,585 per quality-adjusted life-year (QALY) in the whole licensed population and £ 61,204/QALY in the subgroup with low prostate-specific antigen at baseline. The ERG also conducted an incremental analysis comparing sipuleucel-T with both AA and BSC in the chemotherapy-naïve subgroup. Sipuleucel-T had a deterministic ICER of £ 111,682/QALY in this subgroup, when using the ERG's preferred assumptions, and AA was extendedly dominated. The ERG also concluded that estimates of costs and benefits for AA should be interpreted with caution given the limitations of the indirect comparison. The AC noted that the ICER for sipuleucel-T was well above the range usually considered cost effective, and did not recommend sipuleucel-T for the treatment of asymptomatic or minimally symptomatic, metastatic, non-visceral hormone-relapsed prostate cancer.