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P1667: ATTRIBUTES OF RANDOMIZED CONTROLLED TRIALS AND THEIR ASSOCIATIONS WITH FUNDING SOURCE IN VENOUS THROMBOEMBOLISM PROPHYLAXIS FOR PATIENTS WITH CANCER: A BIBLIOGRAPHICAL ANALYSIS

2023· article· en· W4385705882 on OpenAlexaff
Lucy Zhao, Jayhan Kherani, Pei Li, Kevin Zhang, Angelina Horta, Chung‐Wei Christine Lin, Allen Li, Ali Eshaghpour, Mark Crowther

Bibliographic record

VenueHemaSphere · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsUniversity of OttawaUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineRandomized controlled trialSample size determinationMEDLINEExact testPublication biasMeta-analysisConfoundingInternal medicineFamily medicineStatisticsMathematics

Abstract

fetched live from OpenAlex

Topic: 34. Thrombosis and vascular biology - Biology & Translational Research Background: Commercial sponsorship plays a large role in shaping the literature in hematology. Commercial sponsorship has potential to overcome feasibility limitations inherent in randomized controlled trials (RCTs), such as recruitment and duration of follow up, but may attract scrutiny in its robustness or potential for bias. Aims: In RCTs of venous thromboembolism (VTE) prophylaxis in patients with cancer, how do commercially sponsored RCTs compare with non-commercially funded RCTs regarding publication patterns such as reporting bias, robustness, and trial characteristics? Methods: OVID Medline, Embase, and Cochrane CENTRAL, were systematically searched for RCTs that investigated at least one pharmacologic intervention for VTE prophylaxis in adult patients with cancer. Article screening and data extrapolation were conducted in duplicate. Outcomes include a comprehensive set of trial characteristics (e.g. sample size, duration), a favourable outcome, the discrepancy between protocol and manuscript, and appraisal of “spin.” Outcomes were compared using the independent t-test, Mann-Whitney test, Pearson chi-squared test, and Fisher’s exact test where appropriate. Logistic regression was performed to identify factors associated with possible bias. Results: Of the 59 trials analyzed, 34 (63%) reported commercial sponsorship. Commercial sponsorship was not associated with the reporting of favourable outcomes, protocol-manuscript discrepancy, or presence of spin (Chi-squared=0.025, p=0.87; Chi-squared=3.07, p=0.08; Chi-squared=0.20, p=0.65). The commercially sponsored trials had a higher rate of intention-to-treat analysis (Chi-squared=12.2, p=0.0006). In contrast, non-commercially sponsored trials were likelier to report retrospective registration of trial protocol and use of composite primary outcomes (Chi-squared=9.8628, p=0.007; Chi-squared=3.88, p=0.05). Commercial sponsorship was not associated with presence of spin or high levels of spin (Chi-squared=0.20, p=0.65; Chi-squared = 2.52, p=0.11). Spin was most prevalent in the abstract conclusions (9 out of 17 [53.3%]) and manuscript conclusions (8 out of 17 [46.7%]). Summary/Conclusion: There were few significant differences in publication characteristics between commercially sponsored and non-commercially sponsored trials. These results suggest that the evidence from commercially sponsored trials investigating VTE prophylaxis in cancer patients is not likely to be subject to biases attributable to commercial sponsorship.Keywords: Venous thromboembolism, Anticoagulants, Thromboprophylaxis, Cancer

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)0.208
metaresearch head score (Gemma)0.711
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesMetaresearch
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.977

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2080.711
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.017
Bibliometrics0.0440.083
Science and technology studies0.0020.004
Scholarly communication0.0090.007
Open science0.0030.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.074
GPT teacher head0.374
Teacher spread0.300 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainIncentives
GenreEmpirical

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

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