Evidence map›Paper›PMID 25885818›Full record

Observational studyBMC psychiatry2015

Cost-effectiveness of active monitoring versus antidepressants for major depression in primary health care: a 12-month non-randomized controlled trial (INFAP study).

Maria Rubio-Valera, Imma Beneitez, María Teresa Peñarrubia-María, Juan V Luciano, Juan M Mendive, Paul McCrone, Martin Knapp, Ramon Sabés-Figuera, Katarzyna Kocyan, Javier García-Campayo and 1 more

Registry-linked trialOpen access · goldAbstract readControlled Clinical TrialMulticenter StudyObservational Study
In one paragraph

Observational study in BMC psychiatry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02245373 (Cost-effectiveness of a Non-Pharmacological Treatment), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02245373 unknown statusnot on this map

Cost-effectiveness of a Non-Pharmacological Treatment (Active Monitoring) vs. a Pharmacological Treatment for Major Depression in Primary Care. INFAP Study.

Typeobservational_patient_registrySponsorFundació Sant Joan de DéuRan2013 to 2015Enrolled263ConditionsMild to Moderate Depression.ArmsAntidepressants, Active Monitoring
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Use of Mental Health Services for Patients Diagnosed with Major Depressive Disorders in Primary Care.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 7 institutions in 3 countries.

Maria Rubio-ValeraFundació Sant Joan de Déu, Esplugues de Llobregat, Spain. mrubio@pssjd.org.
Imma BeneitezFundació Sant Joan de Déu, Esplugues de Llobregat, Spain. ibeneitez@uoc.edu.
María Teresa Peñarrubia-MaríaPrimary Care Prevention and Health Promotion Research Network (RedIAPP), Barcelona, Spain. 32829mpm@comb.cat.
Juan V LucianoFundació Sant Joan de Déu, Esplugues de Llobregat, Spain. jvluciano@pssjd.org.
Juan M MendivePrimary Care Prevention and Health Promotion Research Network (RedIAPP), Barcelona, Spain. juanmmendive@gmail.com.
Paul McCroneInstitute of Psychiatry, King's College London, De Crespigny Park, London, UK. paul.mccrone@kcl.ac.uk.
Martin KnappPersonal Social Services Research Unit, London School of Economics and Political Science, Houghton Street, London, UK. m.knapp@lse.ac.uk.
Ramon Sabés-FigueraInstitute for Prospective Technological Studies/Joint Research Centre, European Commission, Sevilla, Spain. ramon.sabes-figuera@ec.europa.eu.
Katarzyna KocyanFundació Sant Joan de Déu, Esplugues de Llobregat, Spain. katie.kocyan@gmail.com.
Javier García-CampayoMiguel Servet Hospital, University of Zaragoza, Instituto Aragones de Ciencias de la Salud, Zaragoza, Spain. jgarcamp@gmail.com.
Antoni Serrano-BlancoPrimary Care Prevention and Health Promotion Research Network (RedIAPP), Barcelona, Spain. aserrano@pssjd.org.
Red de Investigación en Actividades Preventivas y Promoción de la Salud · ESUniversitat Oberta de Catalunya · ESEuropean Commission · BEInstituto Aragonés de Ciencias de la Salud · ESKing's College London · GBLondon School of Economics and Political Science · GBSant Joan de Déu Research Foundation · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical practice guidelines for the treatment of major depressive disorder (MDD) recommend antidepressants for patients with moderate-severe depression and active monitoring for patients with mild-moderate symptoms. The feasibility and efficiency of active monitoring has not been proven conclusively. The aim of this study is to evaluate the cost-effectiveness of active monitoring in comparison to antidepressants for primary care patients with mild-moderate MDD. METHODS/

designThis is a 12-month follow-up multicenter observational prospective controlled trial. Patients are enrolled in 12 primary care centers in Barcelona (Spain). Eligible patients are adults (≥18 years-old) with a new episode of MDD that sign a written consent to participate. This is a naturalistic study in which general practitioners (GPs) use their professional judgment to allocate patients into active monitoring or antidepressants groups. GPs treat the patients following their clinical criteria. At baseline, GPs complete a questionnaire (sociodemographic/job characteristics, training, attitude towards depression, interest on mental health and participation in communication groups). Patients' measurements take place at baseline and after six and 12 months. Main outcome measures include severity of depression (PHQ-9), health-related quality of life (EuroQol-5D) and use of healthcare and social care services (Client Service Receipt Inventory). Secondary outcomes include diagnosis of MDD according to DSM-IV diagnostic criteria (SCID-I), disability (WHO-DAS), anxiety (BAI), comorbidities, medication side-effects and beliefs about medicines (BMQ). The analysis will be done according to the intention to treat analysis. Missing data will be imputed using multiple imputation by chained equations. To minimize the bias resulting from the lack of randomization, a propensity score will be used. Incremental effects and costs between groups will be modelled in each of the imputed databases using multivariate generalized linear models and then combined as per Rubin's rules. Propensity scores will be used to adjust the models. Incremental cost-effectiveness ratios will be calculated by dividing the difference in costs between groups by the difference in effects. To deal with the uncertainty, resampling techniques with bootstrapping will be used and cost-effectiveness planes and cost-effectiveness acceptability curves will be constructed. A series of sensitivity analyses will be performed. DISCUSSION: Given the high burden and costs generated by depressive disorder, it is important that general practitioners treat major depression efficiently. Recent evidence has suggested that antidepressants have low benefits for patients with mild to moderate major depression. For such cases of depression, active monitoring exists as a treatment option, but it is not without difficulties for implementation and its effectiveness and efficiency have not been demonstrated conclusively. The results of the study will provide information on which is the most efficient approach to treat patients with mild to moderate major depression in primary care.

trial registrationClinicalTrials.gov: NCT02245373.

Indexed as

AdultAntidepressive AgentsCost-Benefit AnalysisFemaleGeneral PracticeHumansMajor Depressive DisorderMaleMiddle AgedPractice Patterns, Physicians'Prospective StudiesQuality of LifeSpainSurveys and QuestionnairesTreatment OutcomeWatchful WaitingAntidepressive Agents

Identifiers

PMID25885818
PMCPMC4394418
OpenAlexW2003250986

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.