Evidence map›Paper›PMID 20030832›Full record

SynthesisHealth and quality of life outcomes2009

Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008.

Ali Montazeri

2 registry-linked trialsOpen access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Health and quality of life outcomes, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 273 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
273citing papers in PubMed, 11 pooled it
11.4field-weighted citation impact, top 1% 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.

NCT03429296 nacompletednot on this mapstarted 2018, after this paper: background citation

Prospective, Randomized Study Aiming to Assess the Benefit of Autohypnosis Learning in the Care of Patients Treated by Adjuvant Chemotherapy for Colorectal or Breast Cancer.

TypeinterventionalSponsorGroupe Hospitalier Mutualiste de GrenobleRan2018 to 2022Enrolled120ConditionsColorectal Cancer, Breast CancerArmsAutohypnosis learning
NCT07454486 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

TRACE-BTC. Relation of Biomarkers and Patients Reported Quality of Life to Outcomes in Patients With Biliary Tract Cancer: a Real- World Cohort

Typeobservational_patient_registrySponsorAarhus University HospitalRan2026 to 2031Enrolled300ConditionsBiliary Tract Cancer (BTC), Biliary Tract Cancer (CCA), Gall Bladder Cancer, Biliary Tract Cancers (BTC)
3 · Its place in the literature

Who cites it

273 citing papers in PubMed, 11 syntheses or guidelines pooled it, 557 citations in OpenAlex.

  1. Pooled it
  2. Assessing the impact of neoadjuvant chemotherapy and chemoradiotherapy on quality of life during treatment in esophageal cancer: a systematic review and meta-analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Pooled it
  3. Global quality of life and mortality risk in patients with cancer: a systematic review and meta-analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Pooled it
  4. Pooled it
  5. Pooled it
  6. Baseline functioning scales of EORTC QLQ-C30 predict overall survival in patients with gastrointestinal cancer: a meta-analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Pooled it
  7. StrataXRT for the prevention of acute radiation dermatitis in breast cancer: a systematic review and meta-analysis of randomized controlled trials.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Pooled it
  8. Pooled it
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  10. Patient-reported outcomes as predictors of survival in patients with bowel cancer: a systematic review.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2019
    Pooled it
  11. A systematic review of the impact of pain on overall survival in patients with cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2017
    Pooled it
  12. Trial
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  18. Relationship between social support, quality of life, and Th2 cytokines in a biobehavioral cancer survivorship trial.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2019
    Trial
  19. Trial
  20. Quality of life predicts overall survival in women with platinum-resistant ovarian cancer: an AURELIA substudy.Annals of oncology : official journal of the European Society for Medical Oncology · 2017
    Trial

213 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Ali MontazeriIranian Institute for Health Sciences Research, ACECR, Tehran, Iran. montazeri@acecr.ac.ir
Iranian Institute for Health Sciences Research · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth-related quality of life and survival are two important outcome measures in cancer research and practice. The aim of this paper is to examine the relationship between quality of life data and survival time in cancer patients.

methodsA review was undertaken of all the full publications in the English language biomedical journals between 1982 and 2008. The search was limited to cancer, and included the combination of keywords 'quality of life', 'patient reported-outcomes' 'prognostic', 'predictor', 'predictive' and 'survival' that appeared in the titles of the publications. In addition, each study was examined to ensure that it used multivariate analysis. Purely psychological studies were excluded. A manual search was also performed to include additional papers of potential interest.

resultsA total of 451 citations were identified in this rapid and systematic review of the literature. Of these, 104 citations on the relationship between quality of life and survival were found to be relevant and were further examined. The findings are summarized under different headings: heterogeneous samples of cancer patients, lung cancer, breast cancer, gastro-oesophageal cancers, colorectal cancer, head and neck cancer, melanoma and other cancers. With few exceptions, the findings showed that quality of life data or some aspects of quality of life measures were significant independent predictors of survival duration. Global quality of life, functioning domains and symptom scores - such as appetite loss, fatigue and pain - were the most important indicators, individually or in combination, for predicting survival times in cancer patients after adjusting for one or more demographic and known clinical prognostic factors.

conclusionThis review provides evidence for a positive relationship between quality of life data or some quality of life measures and the survival duration of cancer patients. Pre-treatment (baseline) quality of life data appeared to provide the most reliable information for helping clinicians to establish prognostic criteria for treating their cancer patients. It is recommended that future studies should use valid instruments, apply sound methodological approaches and adequate multivariate statistical analyses adjusted for socio-demographic characteristics and known clinical prognostic factors with a satisfactory validation strategy. This strategy is likely to yield more accurate and specific quality of life-related prognostic variables for specific cancers.

Indexed as

Quality of LifeHealth StatusHumansMental HealthMultivariate AnalysisNeoplasmsPrognosisSickness Impact ProfileSurvival Analysis

Identifiers

PMID20030832
PMCPMC2805623
OpenAlexW2028552358

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.