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The impact of early palliative care on the quality of life of patients with advanced pancreatic cancer: The IMPERATIVE study.

2021· article· en· W4246805974 on OpenAlexafffundabout
Christina Kim, Stephanie Lelond, Paul Daeninck, Rasheda Rabbani, Lisa M. Lix, Susan McClement, Harvey Max Chochinov, Benjamin A. Goldenberg

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsGeorge & Fay Yee Centre for Healthcare InnovationUniversity of ManitobaResearch Institute in Oncology and HematologyCancerCare Manitoba
FundersCancerCare Manitoba Foundation
KeywordsMedicineQuality of life (healthcare)Pancreatic cancerPalliative careCancerPerformance statusConfidence intervalAmbulatoryInternal medicineNursing

Abstract

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12116 Background: Pancreatic cancer (PDAC) is an aggressive, deadly disease. Chemotherapy (CT) can improve survival by months, but symptom burden is heavy and quality of life (QOL) is poor. Early palliative care (EPC) alongside standard oncologic care improves QOL and survival in other types of cancer; however, the impact on QOL and symptom burden in advanced PDAC is not known. The primary objective of this study was to test for improvement in QOL between baseline (BL) and 16 weeks (wks) among patients receiving EPC. A secondary objective was to test for decreased symptom burden between BL and 16 wk. Methods: In this prospective case-crossover study, patients >18 years with advanced PDAC received EPC provided by a subspecialist palliative care physician and advanced practice nurse plus standard oncologic care. Ambulatory EPC visits occurred every 2 wks for the first month, then every 4 wks until wk 16, and then as needed. The Functional Assessment of Cancer Therapy – hepatobiliary (FACT-hep) and Edmonton Symptom Assessment System (ESAS) questionnaires were completed at enrollment and every 4 wks until wk 16. Least square means and 95% confidence intervals were computed. A generalized linear mixed model was used to test for statistically significant change in scores between BL and wk 16. A sample size of 20 patients provides 80% power after controlling for covariates; 40 patients were enrolled to account for anticipated attrition and missing data. Results: Of 40 patients, 25 (62.5%) were male, 28 (70%) had metastatic disease, 31 (77.5%) had an ECOG performance status of 0-1, 17 (42.5%) had a body mass index (BMI) >25, 35 (89.7%) had an elevated CA19-9 and 31 (77.5%) received CT. Median age was 70.2 (range 63.0-77.5). BL and wk 16 questionnaires were completed by 100% and 70% of patients, respectively. The mean FACT-hep score at BL was 118.8, compared to 125.7 at wk 16, for a mean change of 6.89, [95%CI (-1.69-15.6); p = 0.11]. The mean change from BL to wk 16 for FACT-hep was statistically significant in patients receiving CT, 10.1 [95%CI (0.32-19.8); p = 0.04], patients with metastatic disease, 14.7 [95%CI (5.30-24.1); p = 0.0030] and patients with a BMI >25, 12.5 [95%CI (1.29-23.7); p = 0.03]. The mean ESAS total symptom score at BL was 25.3, compared to 22.7 at wk 16 (p = 0.28). In those with metastatic disease the mean change was statistically significant, -5.73 [95%CI (-11.21 to -0.24); p = 0.04]. Conclusions: EPC resulted in improved QOL in pts with PDAC receiving CT and those with a BMI >25, and improved QOL and symptom burden in patients with metastatic disease. Given minimal attrition and high rates of questionnaire completion, our sample size was robust, resulting in strong power. Providing palliative care alongside standard oncologic care results in clinically meaningful improvements. Access to palliative care, shortly after diagnosis, should be available for patients with advanced PDAC. Clinical trial information: NCT03837132.

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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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.320
GPT teacher head0.598
Teacher spread0.278 · 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 designObservational
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

Citations4
Published2021
Admission routes3
Has abstractyes

Explore more

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