Evidence map›Paper›PMID 34241700›Full record

Observational studySupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2022

Symptom clusters and their influence on prognosis using EORTC QLQ-C15-PAL scores in terminally ill patients with cancer.

Nanako Koyama, Chikako Matsumura, Yuuna Tahara, Morito Sako, Hideo Kurosawa, Takehisa Nomura, Yuki Eguchi, Kazuki Ohba, Yoshitaka Yano

Open access · hybridAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Nanako KoyamaEducation and Research Center for Clinical Pharmacy, Kyoto Pharmaceutical University, 5 Nakauchi-choYamashina-ku, MisasagiKyoto, 607-8414, Japan.
Chikako MatsumuraEducation and Research Center for Clinical Pharmacy, Kyoto Pharmaceutical University, 5 Nakauchi-choYamashina-ku, MisasagiKyoto, 607-8414, Japan.
Yuuna TaharaEducation and Research Center for Clinical Pharmacy, Kyoto Pharmaceutical University, 5 Nakauchi-choYamashina-ku, MisasagiKyoto, 607-8414, Japan.
Morito SakoDepartment of Pharmacy, Tachibana Medical Corporation Higashisumiyoshi-Morimoto Hospital, Osaka, Japan.
Hideo KurosawaDepartment of Pharmacy, Tachibana Medical Corporation Higashisumiyoshi-Morimoto Hospital, Osaka, Japan.
Takehisa NomuraDepartment of Pharmacy, Tachibana Medical Corporation Higashisumiyoshi-Morimoto Hospital, Osaka, Japan.
Yuki EguchiPalliative Care Unit, Tachibana Medical Corporation Higashisumiyoshi-Morimoto Hospital, Osaka, Japan.
Kazuki OhbaDepartment of Palliative Care, Tachibana Medical Corporation Higashisumiyoshi-Morimoto Hospital, Osaka, Japan.
Yoshitaka YanoEducation and Research Center for Clinical Pharmacy, Kyoto Pharmaceutical University, 5 Nakauchi-choYamashina-ku, MisasagiKyoto, 607-8414, Japan. yano@mb.kyoto-phu.ac.jp.
Fujimoto Pharmaceutical Corporation (Japan) · JPKyoto Pharmaceutical University · JP

Funding

KAKENHI Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science 19K10546
6 · The paper itself

Abstract

purposeThe aims of the present study were to investigate the symptom clusters in terminally ill patients with cancer using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative Care (EORTC QLQ-C15-PAL), and to examine whether these symptom clusters influenced prognosis.

methodsWe analyzed data from 130 cancer patients hospitalized in the palliative care unit from June 2018 to December 2019 in an observational study. Principal component analysis was used to detect symptom clusters using the scored date of 14 items in the QLQ-C15-PAL, except for overall QOL, at the time of hospitalization. The influence of the existence of these symptom clusters and Palliative Performance Scale (PPS) on survival was analyzed by Cox proportional hazards regression analysis, and survival curves were compared between the groups with or without existing corresponding symptom clusters using the log-rank test.

resultsThe following symptom clusters were identified: cluster 1 (pain, insomnia, emotional functioning), cluster 2 (dyspnea, appetite loss, fatigue, and nausea), and cluster 3 (physical functioning). Cronbach's alpha values for the symptom clusters ranged from 0.72 to 0.82. An increased risk of death was significantly associated with the existence of cluster 2 and poor PPS (log-rank test, p = 0.016 and p < 0.001, respectively).

conclusionIn terminally ill patients with cancer, three symptom clusters were detected based on QLQ-C15-PAL scores. Poor PPS and the presence of symptom cluster that includes dyspnea, appetite loss, fatigue, and nausea indicated poor prognosis.

Indexed as

NeoplasmsQuality of LifeHumansPalliative CarePrognosisSurveys and QuestionnairesSyndromeTerminally IllEORTC QLQ-C15-PAL scorePalliative Performance ScaleSurvival predictionSymptom clusterTerminally ill cancer patient

Identifiers

PMID34241700
PMCPMC8636418
OpenAlexW3181332786

What OpenQuestion holds

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Registered trials

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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.