SynthesisBMJ open2024
Variability of quality-of-life measurements and reporting in randomised controlled trials of pancreatic cancer: a systematic review.
Synthesis in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Exploring the Dynamics of Perioperative Quality of Life in Patients with Pancreatic Cancer: A Cross-Lagged Panel Network Analysis.Annals of surgical oncology · 2026Article
- Analysis of the safety and efficacy of laparoscopic gastrojejunostomy following neoadjuvant chemotherapy for gastric pyloric obstruction.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
objectivesThis systematic review aims to evaluate the methodology used in pancreatic cancer (PC) randomised controlled trials (RCTs) measuring quality of life (QOL) and focuses on the type, frequency, survey compliance and duration of these assessments.
designSystematic review of PC RCTs measuring QOL. DATA SOURCES: A search of PubMed.gov and ClinicalTrials.gov was conducted for PC RCTs measuring QOL from inception to 21 March 2023. Only phase III RCTs were included. Studies were excluded if QOL was not measured, the study was phase I/II, in the second-line setting or unavailable in English. Data were independently extracted by two reviewers in a standardised fashion. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes included the type of QOL instrument used, the timing and frequency of assessments, methods of analysis and survey completion rates (SCRs) over time. Secondary outcomes included patient demographics, significant QOL improvements and the frequency of trials measuring QOL.
resultsOut of 269 studies screened, 54 RCTs were identified, and 24 measured QOL (involving 11 229 patients). Instruments used included the EORTC QLQ-C30 (n=15), FACT-HEP (n=3), Spitzer-QOL-Index (n=2), EQ-5D (n=2), LASA (n=1) and FACT-PA (n=1). Most trials assessed QOL until disease progression or death (10/24), with 4-week intervals being the most common (7/24). SCRs were reported in 15/24 trials, with disease stage influencing SCRs over time. In trials with metastatic, locally advanced/metastatic, and resectable disease, the median times to reach a 50% response rate-defined as the point where the number of surveys completed was half of the enrolled participants-were 12.41 weeks (n=2), 14.14 weeks (n=10), and 54.2 weeks (n=3), respectively." Only 2/24 trials reported significant QOL improvements between treatment arms. Patient age was reported in all trials, while race/ethnicity was only reported in 4/24 trials.
conclusionsSignificant variability exists in the timing, methods and reporting of QOL assessments in PC trials. There is a need for further research to assess the implications of missing data and consider the temporality of QOL assessment in patients with advanced cancers and poor prognosis.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.