Examining health-related quality of life patterns in women with breast cancer

Laura C. Pinheiro, Xianming Tan, Andrew F. Olshan, Stephanie B. Wheeler, Katherine E. Reeder-Hayes, Cleo A. Samuel, Bryce B. Reeve

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Abstract

Purpose: We aimed to identify subgroups of women with breast cancer who experience different health-related quality of life (HRQOL) patterns during active treatment and survivorship and determine characteristics associated with subgroup membership. Methods: We used data from the third phase of the population-based Carolina Breast Cancer Study and included 2142 women diagnosed with breast cancer from 2008 to 2013. HRQOL was measured, on average, 5 and 25 months post diagnosis. Latent profile analysis was used to identify HRQOL latent profiles (LPs) at each time point. Latent transition analysis was used to determine probabilities of women transitioning profiles from 5 to 25 months. Multinomial logit models estimated adjusted odds ratios (aORs) and 95% confidence intervals for associations between patient characteristics and LP membership at each time point. Results: We identified four HRQOL LPs at 5 and 25 months. LP1 had the poorest HRQOL and LP4 the best. Membership in the poorest profile at 5 months was associated with younger age aOR 0.95; 0.93–0.96, White race aOR 1.48; 1.25–1.65, being unmarried aOR 1.50; 1.28–1.65 and having public aOR 3.09; 1.96–4.83 or no insurance aOR 6.51; 2.12–20.10. At 25 months, Black race aOR 1.75; 1.18–1.82 was associated with the poorest profile membership. Black race and smoking were predictors of deteriorating to a worse profile from 5 to 25 months. Conclusions: Our results suggest patient-level characteristics including age at diagnosis and race may identify women at risk for experiencing poor HRQOL patterns. If women are identified and offered targeted HRQOL support, we may see improvements in long-term HRQOL and better breast cancer outcomes.

LanguageEnglish (US)
Pages1733-1743
Number of pages11
JournalQuality of Life Research
Volume26
Issue number7
DOIs
StatePublished - Jul 1 2017

Fingerprint

Quality of Life
Breast Neoplasms
Insurance
Survival Rate
Logistic Models
Smoking
Odds Ratio
Confidence Intervals
Population

Keywords

  • Breast cancer
  • Health-related quality of life
  • Latent profiles

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

Cite this

Examining health-related quality of life patterns in women with breast cancer. / Pinheiro, Laura C.; Tan, Xianming; Olshan, Andrew F.; Wheeler, Stephanie B.; Reeder-Hayes, Katherine E.; Samuel, Cleo A.; Reeve, Bryce B.

In: Quality of Life Research, Vol. 26, No. 7, 01.07.2017, p. 1733-1743.

Research output: Contribution to journalArticle

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abstract = "Purpose: We aimed to identify subgroups of women with breast cancer who experience different health-related quality of life (HRQOL) patterns during active treatment and survivorship and determine characteristics associated with subgroup membership. Methods: We used data from the third phase of the population-based Carolina Breast Cancer Study and included 2142 women diagnosed with breast cancer from 2008 to 2013. HRQOL was measured, on average, 5 and 25 months post diagnosis. Latent profile analysis was used to identify HRQOL latent profiles (LPs) at each time point. Latent transition analysis was used to determine probabilities of women transitioning profiles from 5 to 25 months. Multinomial logit models estimated adjusted odds ratios (aORs) and 95{\%} confidence intervals for associations between patient characteristics and LP membership at each time point. Results: We identified four HRQOL LPs at 5 and 25 months. LP1 had the poorest HRQOL and LP4 the best. Membership in the poorest profile at 5 months was associated with younger age aOR 0.95; 0.93–0.96, White race aOR 1.48; 1.25–1.65, being unmarried aOR 1.50; 1.28–1.65 and having public aOR 3.09; 1.96–4.83 or no insurance aOR 6.51; 2.12–20.10. At 25 months, Black race aOR 1.75; 1.18–1.82 was associated with the poorest profile membership. Black race and smoking were predictors of deteriorating to a worse profile from 5 to 25 months. Conclusions: Our results suggest patient-level characteristics including age at diagnosis and race may identify women at risk for experiencing poor HRQOL patterns. If women are identified and offered targeted HRQOL support, we may see improvements in long-term HRQOL and better breast cancer outcomes.",
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