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Record W3083573925 · doi:10.1186/s12916-020-01704-9

Cost-effectiveness of a lifestyle intervention in high-risk individuals for diabetes in a low- and middle-income setting: Trial-based analysis of the Kerala Diabetes Prevention Program

2020· article· en· W3083573925 on OpenAlexaff
Thirunavukkarasu Sathish, Brian Oldenburg, Kavumpurathu Raman Thankappan, Pilvikki Absetz, Jonathan E. Shaw, Robyn J. Tapp, Paul Zimmet, Sajitha Balachandran, Suman Surendra Shetty, Zahra Aziz, Ajay Mahal

Bibliographic record

VenueBMC Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsPopulation Health Research Institute
FundersFogarty International CenterNational Health and Medical Research CouncilMedical Research CouncilEuropean Foundation for the Study of DiabetesNational Institutes of HealthUniversity of MelbourneAmerican Academy of Family Physicians Foundation
KeywordsMedicineCost effectivenessRandomized controlled trialPer capitaGross national incomeDiabetes mellitusIntervention (counseling)Environmental healthGerontologyDemographyGross domestic productPopulationNursingSurgeryEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Data on the cost-effectiveness of lifestyle-based diabetes prevention programs are mostly from high-income countries, which cannot be extrapolated to low- and middle-income countries. We performed a trial-based cost-effectiveness analysis of a lifestyle intervention targeted at preventing diabetes in India. METHODS: The Kerala Diabetes Prevention Program was a cluster-randomized controlled trial of 1007 individuals conducted in 60 polling areas (electoral divisions) in Kerala state. Participants (30-60 years) were those with a high diabetes risk score and without diabetes on an oral glucose tolerance test. The intervention group received a 12-month peer-support lifestyle intervention involving 15 group sessions delivered in community settings by trained lay peer leaders. There were also linked community activities to sustain behavior change. The control group received a booklet on lifestyle change. Costs were estimated from the health system and societal perspectives, with 2018 as the reference year. Effectiveness was measured in terms of the number of diabetes cases prevented and quality-adjusted life years (QALYs). Three times India's gross domestic product per capita (US$6108) was used as the cost-effectiveness threshold. The analyses were conducted with a 2-year time horizon. Costs and effects were discounted at 3% per annum. One-way and multi-way sensitivity analyses were performed. RESULTS: Baseline characteristics were similar in the two study groups. Over 2 years, the intervention resulted in an incremental health system cost of US$2.0 (intervention group: US$303.6; control group: US$301.6), incremental societal cost of US$6.2 (intervention group: US$367.8; control group: US$361.5), absolute risk reduction of 2.1%, and incremental QALYs of 0.04 per person. From a health system perspective, the cost per diabetes case prevented was US$95.2, and the cost per QALY gained was US$50.0. From a societal perspective, the corresponding figures were US$295.1 and US$155.0. For the number of diabetes cases prevented, the probability for the intervention to be cost-effective was 84.0% and 83.1% from the health system and societal perspectives, respectively. The corresponding figures for QALY gained were 99.1% and 97.8%. The results were robust to discounting and sensitivity analyses. CONCLUSIONS: A community-based peer-support lifestyle intervention was cost-effective in individuals at high risk of developing diabetes in India over 2 years. TRIAL REGISTRATION: The trial was registered with Australia and New Zealand Clinical Trials Registry ( ACTRN12611000262909 ). Registered 10 March 2011.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.342
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations34
Published2020
Admission routes1
Has abstractyes

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