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Common and distinct risk factors that influence more severe and distressing shortness of breath profiles in oncology outpatients.
Shin, Joosun; Hammer, Marilyn; Cooley, Mary E; Cooper, Bruce A; Paul, Steven M; Cartwright, Frances; Kober, Kord M; Conley, Yvette P; Levine, Jon D; Miaskowski, Christine.
Affiliation
  • Shin J; Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
  • Hammer M; Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
  • Cooley ME; Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
  • Cooper BA; School of Nursing, University of California, San Francisco, California, USA.
  • Paul SM; School of Nursing, University of California, San Francisco, California, USA.
  • Cartwright F; Mount Sinai Medical Center, New York, New York, USA.
  • Kober KM; School of Nursing, University of California, San Francisco, California, USA.
  • Conley YP; School of Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Levine JD; School of Medicine, University of California, San Francisco, California, USA.
  • Miaskowski C; School of Nursing, University of California, San Francisco, California, USA.
Cancer Med ; 13(3): e7013, 2024 Feb.
Article in En | MEDLINE | ID: mdl-38400684
ABSTRACT

BACKGROUND:

Shortness of breath occurs in 10%-70% of oncology patients. Very little is known about interindividual variability in its severity and distress and associated risk factors. Using latent profile analyses (LPAs), purpose was to identify subgroups of patients with distinct severity and distress profiles for shortness of breath as single symptom dimensions. In addition, a joint LPA was done using patients' severity AND distress ratings. For each of the three LPAs, differences among the shortness of breath classes in demographic, clinical, symptom, stress, and resilience characteristics were evaluated.

METHODS:

Patients completed ratings of severity and distress from shortness of breath a total of six times over two cycles of chemotherapy. All of the other measures were completed at enrollment (i.e., prior to the second or third cycle of chemotherapy). Separate LPAs were done using ratings of severity and distress, as well as a joint analysis using severity AND distress ratings. Differences among the latent classes were evaluated using parametric and nonparametric tests.

RESULTS:

For severity, two classes were identified (Slight to Moderate [91.6%] and Moderate to Severe [8.4%]). For distress, two classes were identified (A Little Bit to Somewhat [83.9%] and Somewhat to Quite a Bit [16.1%]). For the joint LPA, two classes were identified (Lower Severity and Distress [79.9%] and Higher Severity and Distress [20.1%]). While distinct risk factors were associated with each of the LPAs, across the three LPAs, the common risk factors associated with membership in the worse class included a past or current history of smoking, poorer functional status, and higher comorbidity burden. In addition, these patients had a higher symptom burden and higher levels of cancer-specific stress.

CONCLUSIONS:

Clinicians can use the information provided in this study to identify high-risk patients and develop individualized interventions.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Outpatients / Neoplasms Limits: Humans Language: En Journal: Cancer Med Year: 2024 Document type: Article Affiliation country: United States Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Outpatients / Neoplasms Limits: Humans Language: En Journal: Cancer Med Year: 2024 Document type: Article Affiliation country: United States Country of publication: United States