MétaCan
Menu
Back to cohort
Record W4317952775 · doi:10.1093/bjd/ljac140.017

321 Cancer risk with topical pimecrolimus and tacrolimus for atopic dermatitis: systematic review and Bayesian meta-analysis

2023· article· en· W4317952775 on OpenAlexaff
A. Chu, Niveditha Devasenapathy, Melanie Wong, Archita Srivastava, Renata Ceccacci, Clement Lin, Margaret MacDonald, Aaron Wen, Jeremy Steen, Mitchell Levine, Lonnie Pyne, Julie Wang, Jonathan M. Spergel, Jonathan I. Silverberg, Peck Y. Ong, Monica O’Brien, Stephan A Martin, Peter Lio, Mary Laura Lind, Jennifer LeBovidge, Elaine Kim, Joey Huynh, Matthew Greenhawt, Winfred Frazier, Lina Chen, Anna De Benedetto, Mark Boguniewicz, Rachel Asiniwasis, Lynda C. Schneider, Derek K. Chu

Bibliographic record

VenueBritish Journal of Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsUniversity of ReginaUniversity of OttawaUniversity of TorontoMcMaster University
Fundersnot available
KeywordsPimecrolimusMedicineCalcineurinAtopic dermatitisRandomized controlled trialDermatologyTacrolimusRelative riskOdds ratioSkin cancerPopulationMeta-analysisAbsolute risk reductionCancerConfidence intervalInternal medicineEnvironmental healthTransplantation

Abstract

fetched live from OpenAlex

Abstract Atopic dermatitis affects millions worldwide and is effectively managed by topical treatments, including topical calcineurin inhibitors, pimecrolimus and tacrolimus. In 2005 and 2011, the FDA released reviews associating topical calcineurin inhibitors with a theoretical cancer risk, albeit an uncertain association. We systematically reviewed the risk of cancer in patients with atopic dermatitis exposed to topical calcineurin inhibitors. We systematically identified randomized controlled trials, comparative, and non-comparative non-randomized studies from database inception to 6 June 2022, from MEDLINE, EMBASE, GREAT, LILACS, ICTRP, FDA, EMA, company registers and relevant citations. We included studies in any language addressing the risk of cancer in patients with atopic dermatitis exposed to topical calcineurin inhibitors for greater than 3 weeks. We excluded split-body studies. We conducted a Bayesian meta-analysis and used the GRADE approach to determine the certainty of the evidence. A multidisciplinary panel including patients, advocacy groups and care providers, set an a priori threshold of 1 in 1000 risk difference as a clinically important effect. We analysed 121 studies (52 randomized controlled trials and 69 non-randomized studies) including 3.4 million patents followed for a mean of 11 months (range: 0.7–120). The absolute risk of any cancer with topical calcineurin inhibitor exposure was neither different from controls (absolute risk 4.70 per 1000 with topical calcineurin inhibitor exposure vs. 4.56 per 1000 without; odds ratio 1.03 [95% credible interval 0.94–1.11], moderate-certainty evidence) nor the general US population (4.6 per 1000). Findings were similar in infants, children, and adults, and were robust to trial sequential, subgroup and sensitivity analyses. Among infants, children and adults with atopic dermatitis, moderate-certainty evidence shows that topical calcineurin inhibitors do not increase the risk of cancer. These findings support the safe use of topical calcineurin inhibitors in the management of patients with atopic dermatitis. Our findings provide actional information to inform updated clinical practice guidelines, product labels and continuing education for care providers, to clarify the safe usage of topical calcineurin inhibitors.

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)0.024
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.058
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0140.045
Bibliometrics0.0100.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.298
Teacher spread0.277 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of DermatologySame topicDermatology and Skin DiseasesFrench-language works237,207