Evidence map›Paper›PMID 33447956›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2021

Examination of individual and multiple comorbid conditions and health-related quality of life in older cancer survivors.

Elizabeth J Siembida, Ashley Wilder Smith, Arnold L Potosky, Kristi D Graves, Roxanne E Jensen

Registry-linked trialOpen access · bronzeAbstract read
In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07136727 (The Impact of Multimodal Digital Fusion AI-Assisted Decision Support System-Based Comprehensive Management on Clinical Outcomes in County-Level Patients With Comorbid Cancer), which is not on this map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.9field-weighted citation impact, top 12% 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.

NCT07136727 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

The Impact of Multimodal Digital Fusion AI-Assisted Decision Support System-Based Comprehensive Management on Clinical Outcomes in County-Level Patients With Comorbid Cancer:A Prospective Non-randomized Controlled Interventional Study.

TypeinterventionalSponsorThe First Affiliated Hospital of Xinxiang Medical CollegeRan2025 to 2031Enrolled5,000ConditionsOncological Comorbidities (e. g. Hypertension, Diabetes, Malnutrition)ArmsAI-assisted comprehensive management system
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
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

5 authors at 3 institutions in 1 country.

Elizabeth J SiembidaDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA. esiembida@northwell.edu.ORCID http://orcid.org/0000-0003-1131-8359
Ashley Wilder SmithOutcomes Research Branch, National Cancer Institute, Rockville, MD, USA.
Arnold L PotoskyCancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Washington, DC, USA.
Kristi D GravesCancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Washington, DC, USA.
Roxanne E JensenOutcomes Research Branch, National Cancer Institute, Rockville, MD, USA.
National Cancer Institute · USSidney Kimmel Comprehensive Cancer Center · USFeinstein Institute for Medical Research · US

Funding

Validation of PROMIS in Diverse Cancer PopulationsU01AR057971 · NIAMS · GEORGETOWN UNIVERSITY · PI MOINPOUR, CAROL M, POTOSKY, ARNOLD L · 2009 to 2013
$5.7M
NCI NIH HHS U01AR057971NIAMS NIH HHS U01 AR057971
6 · The paper itself

Abstract

purposeOlder cancer survivors (≥ 65 years at diagnosis) are at high-risk for multimorbidity (2 + comorbid conditions). However, few studies have utilized a generalizable sample of older cancer survivors to understand how individual comorbid conditions, as opposed to total comorbidity burden, are associated with health-related quality of life (HRQOL). We examined associations between HRQOL outcomes (pain, fatigue, physical function), individual comorbidities (cardiovascular disease [CVD], lung disease, diabetes, arthritis) and total comorbidity (cancer-only, cancer + 1 condition, cancer + 2 or more conditions).

methodsUtilizing a population-based sample of 2019 older cancer survivors, we tested associations between comorbid conditions and the HRQOL outcomes using generalized linear models. HRQOL domains were assessed using Patient-Reported Outcome Measurement Information System

resultsCancer survivors with lung disease reported significantly worse physical functioning (β = - 4.96, p < 0.001), survivors with arthritis reported significantly higher pain (β = 4.37, p < 0.001), and survivors with CVD reported significantly higher fatigue (β = 3.45, p < 0.001) compared to survivors without each condition. Having cancer + 1 condition was not as strongly associated with all outcomes as when individual conditions were tested (e.g. pain: β = 3.09, p < 0.001). Having 2+ comorbidities had a stronger association with all outcomes (e.g. physical function: β = - 7.51, p < 0.001) than examining conditions individually.

conclusionsKnowing the specific comorbid condition profile of an older cancer survivor provides insight into specific HRQOL outcomes that may be impaired in cancer survivorship, but understanding total comorbidity burden, regardless of the specific conditions, sheds light on survivors at-risk for multiple impairments in HRQOL. This information, taken together, can inform risk-stratified survivorship care.

Indexed as

Patient Reported Outcome MeasuresAgedCancer SurvivorsComorbidityFemaleHumansMaleNeoplasmsQuality of LifeCancerComorbidityHealth-related quality of lifeOlder adultsSymptoms

Identifiers

PMID33447956
PMCPMC7808400
OpenAlexW3119873891

What OpenQuestion holds

Textmetadata
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.