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Record W2492974594 · doi:10.1001/jama.2016.9400

Comparison of Clinical Outcomes and Adverse Events Associated With Glucose-Lowering Drugs in Patients With Type 2 Diabetes

2016· article· en· W2492974594 on OpenAlexaff
Suetonia C. Palmer, Dimitris Mavridis, Antonio Nicolucci, David W. Johnson, Marcello Tonelli, Jonathan C. Craig, Jasjot Maggo, Vanessa Gray, Giorgia De Berardis, Marinella Ruospo, Patrizia Natale, Valeria Saglimbene, Sunil V. Badve, Yeoungjee Cho, Annie‐Claire Nadeau‐Fredette, Michael Burke, Labib Imran Faruque, Anita Lloyd, Nasreen Ahmad, Yuanchen Liu, Sophanny Tiv, Natasha Wiebe, Giovanni FM Strippoli

Bibliographic record

VenueJAMA · 2016
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsRoyal Alexandra HospitalUniversity of AlbertaUniversité de MontréalUniversity of CalgaryHealth Sciences Centre
Fundersnot available
KeywordsMedicineInternal medicineMetforminType 2 diabetesAdverse effectSulfonylureaOdds ratioHypoglycemiaDiabetes mellitusRandomized controlled trialInsulinEndocrinology

Abstract

fetched live from OpenAlex

IMPORTANCE: Numerous glucose-lowering drugs are used to treat type 2 diabetes. OBJECTIVE: To estimate the relative efficacy and safety associated with glucose-lowering drugs including insulin. DATA SOURCES: Cochrane Library Central Register of Controlled Trials, MEDLINE, and EMBASE databases through March 21, 2016. STUDY SELECTION: Randomized clinical trials of 24 weeks' or longer duration. DATA EXTRACTION AND SYNTHESIS: Random-effects network meta-analysis. MAIN OUTCOMES AND MEASURES: The primary outcome was cardiovascular mortality. Secondary outcomes included all-cause mortality, serious adverse events, myocardial infarction, stroke, hemoglobin A1c (HbA1C) level, treatment failure (rescue treatment or lack of efficacy), hypoglycemia, and body weight. RESULTS: A total of 301 clinical trials (1,417,367 patient-months) were included; 177 trials (56,598 patients) of drugs given as monotherapy; 109 trials (53,030 patients) of drugs added to metformin (dual therapy); and 29 trials (10,598 patients) of drugs added to metformin and sulfonylurea (triple therapy). There were no significant differences in associations between any drug class as monotherapy, dual therapy, or triple therapy with odds of cardiovascular or all-cause mortality. Compared with metformin, sulfonylurea (standardized mean difference [SMD], 0.18 [95% CI, 0.01 to 0.34]), thiazolidinedione (SMD, 0.16 [95% CI, 0.00 to 0.31]), DPP-4 inhibitor (SMD, 0.33 [95% CI, 0.13 to 0.52]), and α-glucosidase inhibitor (SMD, 0.35 [95% CI, 0.12 to 0.58]) monotherapy were associated with higher HbA1C levels. Sulfonylurea (odds ratio [OR], 3.13 [95% CI, 2.39 to 4.12]; risk difference [RD], 10% [95% CI, 7% to 13%]) and basal insulin (OR, 17.9 [95% CI, 1.97 to 162]; RD, 10% [95% CI, 0.08% to 20%]) were associated with greatest odds of hypoglycemia. When added to metformin, drugs were associated with similar HbA1C levels, while SGLT-2 inhibitors offered the lowest odds of hypoglycemia (OR, 0.12 [95% CI, 0.08 to 0.18]; RD, -22% [-27% to -18%]). When added to metformin and sulfonylurea, GLP-1 receptor agonists were associated with the lowest odds of hypoglycemia (OR, 0.60 [95% CI, 0.39 to 0.94]; RD, -10% [95% CI, -18% to -2%]). CONCLUSIONS AND RELEVANCE: Among adults with type 2 diabetes, there were no significant differences in the associations between any of 9 available classes of glucose-lowering drugs (alone or in combination) and the risk of cardiovascular or all-cause mortality. Metformin was associated with lower or no significant difference in HbA1C levels compared with any other drug classes. All drugs were estimated to be effective when added to metformin. These findings are consistent with American Diabetes Association recommendations for using metformin monotherapy as initial treatment for patients with type 2 diabetes and selection of additional therapies based on patient-specific considerations.

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)0.027
metaresearch head score (Gemma)0.076
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 score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.076
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.019
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.307
Teacher spread0.288 · 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

Citations418
Published2016
Admission routes1
Has abstractyes

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