The utility of patient reported data in a gynecologic oncology clinic View Full Text


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Article Info

DATE

2018-12

AUTHORS

D. Barnes, R. Rivera, S. Gibson, C. Craig, J. Cragun, B. Monk, D. Chase

ABSTRACT

Background: Measuring QoL is essential to the field of gynecologic oncology but there seems to be limited standardized data regarding collecting QoL assessments throughout a patient's cancer treatment especially in non-clinical trial patients. The aim of this study is to explore patient characteristics that may be associated with poor quality of life (QoL) in women with gynecologic cancers at two University of Arizona Cancer Center (UACC) sites. Methods: A cross-sectional survey was conducted among English speaking women with gynecologic malignancies at the University of Arizona Cancer Centers in Phoenix and Tucson from April 2012 to July 2015. The survey was a paper packet of questions that was distributed to cancer patients at the time of their clinic visit. The packet contained questions on demographic information, treatment, lifestyle characteristics, pelvic pain and Health-related quality of life (HRQoL). Measures included the generic and cancer-specific scores on the Functional Assessment of Cancer Therapy-General (FACT-G) and the Female Genitourinary Pain Index (GUPI). The total scores and subdomains were compared with descriptive variables (age, body mass index (BMI), diet, exercise, disease status, treatment and support group attendance) using Cronbach alpha (α), Spearman rank correlations (ρ), and Holm's Bonferroni method. Results: One-hundred and forty-nine women completed the survey; 55% (N = 81) were older than 60 years, 38% (N = 45) were obese (BMI > 30), 46% (N = 66) exercised daily, and 84% (N = 111) ate one or more daily serving of fruit and vegetables. Women in remission, those who exercised daily and ate fruits/vegetables were less likely to have their symptoms impact their QoL. Younger women were more likely to report genitourinary issues (p = - 0.22) and overall problems with QoL (p = - 0.29) than older women. Among FACT-G support group responses, we found those that did not attend support groups had a significantly higher emotional wellbeing (p = 0.05). Conclusions: This study identified potential areas of clinical focus, which aid in understanding our approach to caring for gynecologic cancer patients and improvement of their HRQoL. We identified that age, pelvic pain, and lifestyle characteristics have indicators to poor QoL in women with gynecologic cancers. In this population, younger women and those with pelvic pain complaints, poor diet and exercise habits should be targeted early for supportive care interventions to improve QoL throughout both treatment and survivorship. More... »

PAGES

4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s40661-018-0062-4

DOI

http://dx.doi.org/10.1186/s40661-018-0062-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105563378

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30009038


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    "description": "Background: Measuring QoL is essential to the field of gynecologic oncology but there seems to be limited standardized data regarding collecting QoL assessments throughout a patient's cancer treatment especially in non-clinical trial patients. The aim of this study is to explore patient characteristics that may be associated with poor quality of life (QoL) in women with gynecologic cancers at two University of Arizona Cancer Center (UACC) sites.\nMethods: A cross-sectional survey was conducted among English speaking women with gynecologic malignancies at the University of Arizona Cancer Centers in Phoenix and Tucson from April 2012 to July 2015. The survey was a paper packet of questions that was distributed to cancer patients at the time of their clinic visit. The packet contained questions on demographic information, treatment, lifestyle characteristics, pelvic pain and Health-related quality of life (HRQoL). Measures included the generic and cancer-specific scores on the Functional Assessment of Cancer Therapy-General (FACT-G) and the Female Genitourinary Pain Index (GUPI). The total scores and subdomains were compared with descriptive variables (age, body mass index (BMI), diet, exercise, disease status, treatment and support group attendance) using Cronbach alpha (\u03b1), Spearman rank correlations (\u03c1), and Holm's Bonferroni method.\nResults: One-hundred and forty-nine women completed the survey; 55% (N\u2009=\u200981) were older than 60\u00a0years, 38% (N\u2009=\u200945) were obese (BMI >\u200930), 46% (N\u2009=\u200966) exercised daily, and 84% (N\u2009=\u2009111) ate one or more daily serving of fruit and vegetables. Women in remission, those who exercised daily and ate fruits/vegetables were less likely to have their symptoms impact their QoL. Younger women were more likely to report genitourinary issues (p\u2009=\u2009-\u20090.22) and overall problems with QoL (p\u2009=\u2009-\u20090.29) than older women. Among FACT-G support group responses, we found those that did not attend support groups had a significantly higher emotional wellbeing (p\u2009=\u20090.05).\nConclusions: This study identified potential areas of clinical focus, which aid in understanding our approach to caring for gynecologic cancer patients and improvement of their HRQoL. We identified that age, pelvic pain, and lifestyle characteristics have indicators to poor QoL in women with gynecologic cancers. In this population, younger women and those with pelvic pain complaints, poor diet and exercise habits should be targeted early for supportive care interventions to improve QoL throughout both treatment and survivorship.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s40661-018-0062-4'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s40661-018-0062-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s40661-018-0062-4'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s40661-018-0062-4'


 

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