MétaCan
Menu
← Back to cohort

Alleviating breathlessness in patients with cancer with dexamethasone (ABCD): A parallel-group, double-blind, randomized clinical trial (RCT).

2022· article· en· W4286297624 on OpenAlexaboutno aff
David S.C. Hui, Veronica Puac, Zeena Shelal, Rony Dev, Sandra K. Hanneman, Kristofer Jennings, Y. Hilary, Diana L. Urbauer, Sanjay Shete, Frank V. Fossella, Zhongxing Liao, George R. Blumenschein, Joe Y. Chang, Michael S. O’Reilly, Saumil Gandhi, Anne S. Tsao, Donald A. Mahler, Éduardo Bruera

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsMedicineRandomized controlled trialDexamethasoneRandomizationPlaceboInternal medicineAdverse effectAmbulatoryPhysical therapy

Abstract

fetched live from OpenAlex

12112 Background: Systemic corticosteroids are commonly prescribed for palliation of dyspnea in patients with cancer; however, evidence to support their use is limited. A small RCT suggested that dexamethasone may be efficacious. In this confirmatory RCT, we compared the effect of high dose dexamethasone and placebo on dyspnea in patients with cancer. Methods: This NCI-funded, multi-site, double-blind, parallel group RCT enrolled ambulatory patients with cancer, age ≥18, dyspnea ≥4/10 and randomly assigned them to receive dexamethasone 8 mg orally every 12 hours for 7 days followed by 4 mg orally every 12 hours for 7 days or matching placebo capsules. Permuted block randomization (block size = 6, 2:1) was conducted, stratified by baseline dyspnea and study site. Patients, research staff and clinicians were blinded. The primary outcome was change in average dyspnea intensity assessed with a 0-10 numeric rating scale (0 = none, 10 = worst) between baseline and day 7. Secondary outcomes included the Edmonton Symptom Assessment Scale (ESAS) and adverse effects (CTCAE v4.02). Intention-to-treat analysis was conducted with linear models to compare between groups. The planned sample size of 201 patients provided 80% power to detect a mean difference of 1.0 between treatment groups with a two-sided α of 5%, assuming a standard deviation of 2.0 and 15% attrition. (Clinicaltrials.gov NCT03367156). Results: Between 1/11/2017 and 4/23/2021, we enrolled 149 patients and 128 received the blinded study interventions (dexamethasone n = 85, placebo n = 43). Enrollment was terminated early by the Data Safety Monitoring Board when futility criterion was met in pre-planned interim analysis. The mean change in dyspnea NRS intensity between baseline and day 7 was -1.6 (95% CI -2, -1.2) in the dexamethasone group and -1.6 (95% CI -2.3, -0.9) in the placebo group, with no significant between-group difference (mean 0, 95% CI -0.8, 0.7; P = 0.91). Secondary analyses showed that the dexamethasone group had a significantly better ESAS appetite (mean difference -1.2, 95% CI -2.2, -0.1; P = 0.03) and well being (mean -1, 95% CI -1.8, -0.2; P = 0.02), and worse ESAS anxiety (mean 1.1, 95% CI 0.3, 1.9; P = 0.01) and depression (mean 0.9, 95% CI 0.1, 1.7; P = 0.02) compared to placebo. Similar magnitude of changes in dyspnea and ESAS symptoms were observed by day 14. Adverse effects were reported more frequently in the dexamethasone group (any grade): insomnia (38% v. 12%), neuropsychiatric symptoms (31% vs. 7%), infections (21% v. 12%), dyspepsia (26% v. 12%), edema (18% v. 9%), hiccups (12% v. 7%), flushing (9% v. 5%) and respiratory distress (6% v. 0%). More patients in the dexamethasone group required hospitalization within 30 d of last study medication (25% vs. 7%, P = 0.02). Conclusions: High dose dexamethasone did not improve dyspnea in patients with cancer more than placebo and was associated with more adverse events. Clinical trial information: NCT03367156.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.138
GPT teacher head0.464
Teacher spread0.326 · 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 designRandomized trial
Domainnot available
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicCancer survivorship and care→French-language works237,207→