Values, preferences and burden of treatment for the initiation of GLP-1 receptor agonists and SGLT-2 inhibitors in adult patients with type 2 diabetes: a systematic review
Bibliographic record
Abstract
OBJECTIVES: Assess values, preferences and burden of treatment that patients with type 2 diabetes consider when initiating glucagon-like peptide-1 receptor agonists (GLP-1 RA) or sodium-glucose cotransporter-2 inhibitors (SGLT-2i) compared with other glucose-lowering options. METHODS: Paired reviewers independently included studies reporting quantitative or qualitative methods to assess values, preferences and burden of treatment reported by patients with type 2 diabetes regarding the initiation of GLP-1 RA or SGLT-2i over other alternatives. A systematic search in MEDLINE, Scopus, EMBASE, Web of Science and Cochrane Central Register of Controlled Trials from inception until May 2020 was performed by an experienced librarian. Risk of bias was assessed with a specifically designed tool for values and preferences studies. RESULTS: 17 studies (7296 patients) proved eligible. Studies fulfilling criteria for SGLT-2i were not identified. Five studies (2662 patients) evaluated preferences for GLP-1 RA compared with other glucose-lowering medications. 12 studies (4634 patients) evaluated preferences between, at least, two kinds of GLP-1 RA or their injection devices based on the following attributes: efficacy, dose, application frequency, device characteristics. Among studies comparing GLP-1 RA to other glucose-lowering medications, some preferences were observed for dypeptil peptidase-4 inhibitors compared with once daily liraglutide. Comparing different attributes of GLP-1 RA drugs and devices, cardiovascular risk reduction, glucose lowering potential, once weekly and simple administered regimens were the most preferred. CONCLUSIONS: As no evidence for preferences on SGLT-2i was available, only preferences for GLP-1 RA were assessed; however, evidence is still limited for the latter. Studies comparing preferences for GLP1-RA to other glucose-lowering alternatives only included twice daily or once daily injection regimens of GLP-1 RA drugs. According to our findings, once weekly alternatives are widely preferred than the formers. The extent to which patients with type 2 diabetes value reduced adverse cardiovascular and kidney outcomes, weighed benefits against harms and burden of treatment is limited and with very low certainty. PROSPERO REGISTRATION NUMBER: CRD42020159284.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".