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Record W2736124202 · doi:10.1186/s13643-017-0540-5

Anorexia nervosa and cancer: a protocol for a systematic review and meta-analysis of observational studies

2017· review· en· W2736124202 on OpenAlexafffundabout
Ferrán Catalá-López, Brian Hutton, Jane A. Driver, Manuel Ridao-López, José M Valderas, Ricard Gènova-Maleras, Jaume Forés-Martos, Adolfo Alonso‐Arroyo, Diego Macías Saint-Gerons, Eduard Vieta, Alfonso Valencia, Rafael Tabarés‐Seisdedos

Bibliographic record

VenueSystematic Reviews · 2017
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersCanadian Institutes of Health ResearchCentro de Investigación Biomédica en Red de Salud MentalGeneralitat Valenciana
KeywordsAnorexia nervosaMedicineObservational studyPsychosocialMeta-analysisCancerPsychiatrySystematic reviewEating disordersMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Anorexia nervosa is characterized by a severe restriction of caloric intake, low body weight, fear of gaining weight or of becoming fat, and disturbance of body image. Pathogenesis of the disorder may include genetic predisposition, hormonal changes and a combination of environmental, psychosocial, and cultural factors. Cancer is the second leading cause of death worldwide. At present, no systematic reviews and meta-analyses have evaluated the risk of cancer in people with anorexia nervosa. The objective of this study will be to evaluate the association between anorexia nervosa and the risk of developing or dying from cancer. METHODS/DESIGN: This study protocol is part of a systematic collection and assessment of multiple systematic reviews and meta-analyses (umbrella review) evaluating the association of cancer and multiple central nervous system disorders. We designed a specific protocol for a new systematic review and meta-analysis of observational studies of anorexia nervosa with risk of developing or dying from any cancer. Data sources will be PubMed, Embase, Scopus, Web of Science, and manual screening of references. Observational studies (case-control and cohort) in humans that examined the association between anorexia nervosa and risk of developing or dying from cancer will be sought. The primary outcomes will be cancer incidence and cancer mortality in association with anorexia nervosa. Secondary outcomes will be site-specific cancer incidence and mortality, respectively. Screening of abstracts and full texts, and data abstraction will be performed by two team members independently. Conflicts at all levels of screening and abstraction will be resolved through discussion. The quality of studies will be assessed by using the Ottawa-Newcastle scale by two team members independently. Random effects models will be conducted where appropriate. Subgroup and additional analyses will be conducted to explore the potential sources of heterogeneity. The World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) criteria and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be used for determining the quality of evidence for cancer outcomes. DISCUSSION: Findings from this systematic review will inform an ongoing umbrella review on cancer and central nervous system disorders. Our systematic review and meta-analysis of observational studies will establish the extent of the epidemiological evidence underlying the association between anorexia nervosa and cancer. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017067462.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.102
metaresearch head score (Gemma)0.176
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.102
Threshold uncertainty score0.541

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1020.176
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0190.026
Bibliometrics0.0130.017
Science and technology studies0.0040.004
Scholarly communication0.0070.006
Open science0.0060.005
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0600.007

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 head0.696
GPT teacher head0.592
Teacher spread0.104 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations10
Published2017
Admission routes3
Has abstractyes

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