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Early Integrated Palliative Care in Patients With Advanced Cancer

2024· article· en· W4401420234 on OpenAlexaboutno aff
EunKyo Kang, Jung Hun Kang, Su‐Jin Koh, Yu Jung Kim, Seyoung Seo, Jung Hoon Kim, Jaekyung Cheon, Eun Joo Kang, Eun‐Kee Song, Eun Mi Nam, Ho-Suk Oh, Hye Jin Choi, Jung Hye Kwon, Woo Kyun Bae, Jeong Eun Lee, Kyung Hae Jung, Young Ho Yun

Bibliographic record

VenueJAMA Network Open · 2024
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
FundersKorea Health Industry Development Institute
KeywordsMedicinePalliative careRandomized controlled trialQuality of life (healthcare)Psychological interventionCoping (psychology)CancerClinical trialCoachingPhysical therapyFamily medicineNursingInternal medicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

Importance: Limited data suggest that early palliative care (EPC) improves quality of life (QOL) and survival in patients with advanced cancer. Objective: To evaluate whether comprehensive EPC improves QOL; relieves mental, social, and existential burdens; increases survival rates; and helps patients develop coping skills. Design, Setting, and Participants: This nonblinded randomized clinical trial (RCT) recruited patients from 12 hospitals in South Korea from September 2017 to October 2018. Patients aged 20 years or older with advanced cancer who were not terminally ill but for whom standard chemotherapy has not been effective were eligible. Participants were randomized 1:1 to the control (receiving usual supportive oncological care) or intervention (receiving EPC with usual oncological care) group. Intention-to-treat data analysis was conducted between September and December 2022. Interventions: The intervention group received EPC through a structured program of self-study education materials, telephone coaching, and regular assessments by an integrated palliative care team. Main Outcomes and Measures: The primary outcome was the change in overall QOL score (assessed with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative Care) from baseline to 24 weeks after enrollment, with evaluations also conducted at 12 and 18 weeks. Secondary outcomes were social and existential burdens (assessed with the McGill Quality of Life Questionnaire) as well as crisis-overcoming capacity and 2-year survival. Results: A total of 144 patients (83 males [57.6%]; mean [SD] age, 60.7 (7.2) years) were enrolled, of whom 73 were randomized to the intervention group and 71 to the control group. The intervention group demonstrated significantly greater changes in scores in overall health status or QOL from baseline, especially at 18 weeks (11.00 [95% CI, 0.78-21.22] points; P = .04; effect size = 0.42). However, at 12 and 24 weeks, there were no significant differences observed. Compared with the control group, the intervention group also showed significant improvement in self-management or coping skills over 24 weeks (20.51 [95% CI, 12.41-28.61] points; P < .001; effect size = 0.93). While the overall survival rate was higher in the intervention vs control group, the difference was not significant. In the intervention group, however, those who received 10 or more EPC interventions (eg, telephone coaching sessions and care team meetings) showed a significantly increased probability of 2-year survival (53.6%; P < .001). Conclusions and Relevance: This RCT demonstrated that EPC enhanced QOL at 18 weeks; however, no significant improvements were observed at 12 and 24 weeks. An increased number of interventions sessions was associated with increased 2-year survival rates in the intervention group. Trial Registration: ClinicalTrials.gov Identifier: NCT03181854.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.396
Teacher spread0.345 · 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

Citations44
Published2024
Admission routes1
Has abstractyes

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