Abstract
Context.
Shortness of breath is a distressing symptom that occurs in 10% to 70% of oncology patients. Despite this broad range in its occurrence, little is known about inter-individual variability in shortness of breath and associated risk factors among patients receiving chemotherapy.
Objectives.
Identify subgroups of patients with distinct shortness of breath profiles; evaluate for differences among these subgroups in demographic and clinical characteristics; evaluate for differences among symptom dimensions of shortness of breath, and evaluate for differences in quality of life outcomes.
Methods.
Outpatients (n=1338) completed questionnaires six times over two chemotherapy cycles. Occurrence of shortness of breath was assessed using the Memorial Symptom Assessment Scale. Latent class analysis was used to identify subgroups of patients with distinct shortness of breath profiles.
Results.
Four distinct shortness of breath profiles were identified (None [70.5%], Decreasing [8.2%], Increasing [7.8%], High [13.5%]). Risk factors for membership in High class included: history of smoking, self-reported diagnosis of lung disease, having lung cancer, and receipt of a higher number of cancer treatments. Compared to the None class, High class reported poorer physical, psychological, and social functioning.
Conclusions.
Almost 14% of patients with heterogeneous types of cancer receiving chemotherapy had persistently high occurrence rates of shortness of breath for almost two months. In addition, compared to the Decreasing and Increasing classes, the High class’ episodes of shortness of breath were more frequent and more severe. Clinicians need to assess all oncology patients for shortness of breath and provide targeted interventions.
Keywords: Cancer, cough, dyspnea, latent class analysis, patient-reported outcomes, quality of life
Introduction
Shortness of breath is a common and distressing symptom that occurs in approximately 10% to 90% of oncology patients.1–4 While many clinicians attribute this symptom to the lung cancer itself, three cross-sectional studies demonstrated that shortness of breath is prevalent in other types of cancer.2,5,6 Patients can experience shortness of breath as a result of the cancer itself, associated treatments (e.g., pulmonary toxicities7), and/or cardiopulmonary conditions.2,5,6
The broad range in prevalence rates suggests that a large amount of inter-individual variability exists in this symptom.1 While two longitudinal studies found that individual trajectories of shortness of breath varied,4,8 and numerous demographic and clinical characteristics impacted this variability,4 these studies evaluated patients with advanced cancer receiving palliative care near the end of life. Therefore, additional research is needed on the occurrence, severity, distress, and risk factors for shortness of breath in patients with heterogenous types of cancer undergoing active treatment.
In our recent systematic review,9 only three studies examined factors associated with the occurrence of shortness of breath in patients with lung3,10 or advanced11 cancer. Older age,3 being unemployed,3 having fewer years of education,3 not engaging in moderate to strenuous physical activity,3 having a history of tobacco use,3,10 lower performance status,10 and the presence of pulmonary comorbidity3,10 as well as lower pulmonary function test scores,3,10 were associated with higher rates of shortness of breath. None of these three studies used a comprehensive list of potential risk factors for shortness of breath in patients receiving chemotherapy. In addition, while data from lung cancer patients suggest that cough and chest tightness are common respiratory symptoms that co-occur with shortness of breath,12–14 none of the studies cited above3,10,11 evaluated for associations between shortness of breath and other respiratory symptoms in oncology patients receiving chemotherapy.
Shortness of breath is a multidimensional symptom that warrants investigation using the domains of sensory-perceptual experience (i.e., intensity), affective distress, and impact (e.g., quality of life (QOL)).15 However, as noted in our review,9 the majority of studies focused primarily on the severity of shortness of breath. In addition, while an evaluation of the overall impact of shortness of breath on oncology patients’ physical and psychological functioning is important,15 no studies have done a comprehensive examination of multiple domains of QOL. This lack of knowledge regarding the multiple dimensions of the symptom experience of shortness of breath in the same sample of oncology patients will be addressed in the current study.
Latent class analysis (LCA) is a person-centered analytic approach that can be used to identify subgroups (i.e., latent classes) of patients with distinct symptom profiles.16 Given the variability in the occurrence rates of shortness of breath among oncology outpatients, the use of LCA may provide insights into modifiable and non-modifiable risk factors that contribute to its interindividual variability.17 Therefore, the purposes of this study, in a sample of oncology outpatients receiving chemotherapy (n=1338), were to: identify subgroups of patients with distinct shortness of breath profiles; evaluate for differences among the subgroups in demographic and clinical characteristics; evaluate for differences in frequency, severity, and distress of shortness of breath; evaluate for differences in the co-occurrence of other common respiratory symptoms; and evaluate for differences in the QOL outcomes.
Methods
Patients and Settings
This study is part of a larger, longitudinal study of the symptom experience of oncology outpatients receiving chemotherapy.18 Eligible patients were ≥18 years of age; had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; were scheduled to receive at least two additional cycles of chemotherapy; were able to read, write, and understand English; and gave written informed consent. Patients were recruited from two Comprehensive Cancer Centers, one Veteran’s Affairs hospital, and four community-based oncology programs during their first or second cycle of chemotherapy. The major reason for refusal was being overwhelmed with their cancer treatment.
Study Procedures
This study was approved by the Institutional Review Board at each of the study sites. Of the 2234 patients approached, 1343 consented to participate (60.1% response rate). Of these 1343 patients, 1338 rated the occurrence of shortness of breath a total of six times over two chemotherapy cycles (i.e., prior to chemotherapy administration (assessments 1 and 4), approximately 1 week after chemotherapy administration (assessments 2 and 5), and approximately 2 weeks after chemotherapy administration (assessments 3 and 6)). Patients completed the other measures used in this analysis at enrollment (i.e., prior to patients’ second or third cycle of chemotherapy).
Instruments
Demographic and Clinical Measures.
Patients completed a demographic questionnaire, Karnofsky Performance Status (KPS) scale,19 Self-Administered Comorbidity Questionnaire (SCQ),20 Alcohol Use Disorders Identification Test (AUDIT),21 and smoking history questionnaire. Level of exercise was assessed using an investigator developed questionnaire. Using the recommendation for physical activity from the Office of Disease Prevention and Health Promotion’s Healthy People 2020 report,22 patients’ responses were categorized into one of three exercise groups (i.e., no exercise, <150 minutes per week, ≥150minutes per week).23 Medical records were reviewed for disease and treatment information.
Measure of Shortness of Breath and Co-occurring Respiratory Symptoms.
The shortness of breath item from the Memorial Symptom Assessment Scale (MSAS) was used to assess for the occurrence of shortness of breath at each of the six assessments. Frequency, severity, and distress of shortness of breath were evaluated using data from the enrollment assessment. In addition, the occurrence rates for chest tightness, difficulty breathing, and cough at enrollment were evaluated. Validity and reliability of the MSAS are well established.24
Measures of QOL.
Disease-specific and generic measures of QOL were used in this study. Disease-specific QOL was evaluated using the Multidimensional QOL Scale-Patient Version (MQOLS-PV).25 This 41-item instrument measures four domains of QOL (i.e., physical, psychological, social, spiritual well-being) in oncology patients, as well as a total QOL score.
The Medical Outcomes Study-Short Form (SF-12) was the generic measure of QOL that consists of 12 questions about physical and mental health as well as overall health status. The SF-12 was scored into two components that measure physical (Physical Component Summary (PCS)) and psychological (Mental Component Summary (MCS)) function. These scores can range from 0 to 100. Higher PCS and MCS scores indicate better physical and psychological functioning, respectively.
Data Analysis
Descriptive statistics and frequency distributions were generated for sample characteristics at enrollment using the Statistical Package for the Social Sciences (SPSS) version 28 (IBM Corporation, Armonk, NY). As was done previously,26 unconditional LCA was used to identify distinct shortness of breath profiles that characterized unobserved subgroups of patients (i.e., latent classes) over the six assessments. Before performing the LCA, patients who reported the occurrence of shortness of breath for ≤1 of the six assessments were identified and labeled as the “None” class (n=943, 70.5%). Then, the LCA was performed on the remaining 395 patients using MPlus™ Version 8.4.27
Estimation was carried out with full information maximum likelihood with standard error and a Chi square test that are robust to non-normality and non-independence of observations (“estimator=MLR”). Model fit was evaluated to identify the solution that best characterized the observed latent class structure with the Bayesian Information Criterion (BIC), Vuong-Lo-Mendell-Rubin likelihood ratio test (VLRM), entropy, and latent class percentages that were large enough to be reliable.28 Missing data were accommodated for with the use of the Expectation-Maximization (EM) algorithm.29
Differences among the latent classes in demographic, clinical, and symptom characteristics, as well as QOL outcomes, were evaluated using parametric and nonparametric tests. A p-value of <.05 was considered statistically significant. Post hoc contrasts were done using a Bonferroni corrected p-value of <.008 (.05/6 possible pairwise comparisons).
Results
Latent Class Analysis
The 943 patients (70.5%) who had ≤1 occurrence of shortness of breath over the six assessments were classified as the None class. For the remaining 395 patients whose data were entered into the LCA, a three-class solution was selected because the 3-class solution fit the data better than the 2- and 4 class solutions (see Table 1 for details).
Table 1.
Shortness of Breath Occurrence Latent Class Solutions and Fit Indices for One Through Four Classes.
| Model | LL | AIC | BIC | Entropy | VLMR |
|---|---|---|---|---|---|
|
| |||||
| 1 Class | −1325.86 | 2663.72 | 2687.60 | n/a | n/a |
| 2 Class | −1262.46 | 2550.93 | 2602.65 | 0.66 | 126.80a |
| 3 Classc | −1210.75 | 2461.50 | 2541.08 | 0.66 | 103.43b |
| 4 Class | −1204.76 | 2463.51 | 2570.94 | 0.73 | Ns |
Abbreviations: AIC = Akaike’s Information Criterion; BIC = Bayesian Information Criterion; LL = log-likelihood; n/a = not applicable; ns = not significant, VLMR = Vuong-Lo-Mendell-Rubin likelihood ratio test for the K vs. K-1 model Baseline entropy and VLMR are not applicable for the one-class solution
P =.0001
P < .00005
The 3-class solution was selected because the BIC for that solution was lower than the BIC for the 2-class solution. In addition, the VLMR was significant for the 3-class solution, indicating that three classes fit the data better than two classes. The BIC increased for the 4-class compared to the 3-class solution, indicating that the fit of the 4-class solution was worse. Further, the VLMR was not significant for the 4-class solution, indicating that too many classes had been extracted.
Fig. 1 displays the trajectories for the occurrence of shortness of breath among the latent classes. For the decreasing class (8.2%), the occurrence rates for shortness of breath decreased from the first to the fourth assessments; dramatically decreased from the fourth to the fifth assessments; and then increased slightly from the fifth to sixth assessments. For the increasing class (7.8%), the occurrence rates for shortness of breath decreased slightly from the first to second assessments; increased gradually from the second to the fifth assessments; and decreased slightly to the sixth assessment. For the High class (13.5%), while slightly higher rates were reported at assessments 2 and 5, the occurrence rates for shortness of breath remained consistently high over the six assessments.
Fig. 1.
Trajectories of shortness of breath occurrence for the four latent classes.
Demographic and Clinical Characteristics
Compared to the None class, High class was more likely to live alone, less likely to be employed, and more likely to report a previous or current history of smoking (Table 2). In addition, they were more likely to have multiple cancer treatments, more likely to have lung metastasis, more likely to be receiving chemotherapy on 21- or 28-day cycles, and more likely to self-report a diagnosis of osteoarthritis, back pain, and rheumatoid arthritis. Compared to the None class, Decreasing and High classes had lower KPS scores, a higher number of comorbidities, higher SCQ scores, and were more likely to self-report a diagnosis of depression. Compared to the None and Decreasing classes, High class was more likely to be older and more likely to have lung cancer.
Table 2.
Differences in Demographic and Clinical Characteristics at Enrollment Among the Shortness of Breath Latent Classes.
| Characteristic | None (0) 70.5% (n = 943) Mean (SD) |
Decreasing (1) 8.2% (n = 109) Mean (SD) |
Increasing (2) 7.8% (n = 105) Mean (SD) |
High (3) 13.5 % (n=181) Mean (SD) |
Statistics |
|---|---|---|---|---|---|
|
| |||||
| Age (years) | 57.0 (12.3) | 55.3 (13.0) | 56.5 (12.2) | 59.6 (12.0) | F = 3.44, P = .016 0 and 1 < 3 |
| Education (years) | 16.3 (3.0) | 15.8 (2.8) | 16.1 (3.0) | 16.2 (3.1) | F = 0.69, P = .558 |
| Body mass index (kilogram/meter squared) | 25.9 (5.4) | 26.2 (6.4) | 27.4 (6.5) | 26.8 (6.0) | F = 3.05, P = .028 no significant pairwise contrasts |
| Alcohol use disorders identification test score | 3.1 (2.5) | 2.9 (2.3) | 2.5 (2.5) | 2.8 (2.5) | F = 1.11, P = .346 |
| Karnofsky performance status score | 81.7 (12.0) | 75.4 (12.4) | 78.9 (12.9) | 74.7 (12.7) | F = 21.31, P <.001 0 > 1 and 3, 2 > 3 |
| Number of comorbid conditions | 2.2 (1.3) | 2.7 (1.6) | 2.5 (1.5) | 3.1 (1.6) | F = 21.05, P <.001 0 < 1 and 3, 2 < 3 |
| Self-administered comorbidity questionnaire score | 5.1 (2.8) | 6.2 (3.5) | 5.8 (3.6) | 7.1 (4.0) | F = 24.27, P <.001 0 < 1 and 3, 2 < 3 |
| Time since diagnosis (years) | 1.7 (3.2) | 2.7 (5.5) | 2.3 (4.0) | 2.8 (5.3) | KW = 10.42, P = .015 no significant pairwise contrasts |
| Time since diagnosis (years, median) | 0.41 | 0.50 | 0.44 | 0.51 | |
| Number of prior cancer treatments | 1.5 (1.4) | 1.9 (1.7) | 1.7 (1.5) | 1.8 (1.7) | F = 4.27, P = .005 0 < 3 |
| Number of metastatic sites including lymph node involvementa | 1.2 (1.2) | 1.2 (1.2) | 1.3 (1.2) | 1.4 (1.4) | F = 1.06, P = .365 |
| Number of metastatic sites excluding lymph node involvement | 0.8 (1.0) | 0.8 (1.0) | 0.8 (1.1) | 1.0 (1.2) | F = 1.84, P = .138 |
| MAX2 score | 0.17 (0.08) | 0.17 (0.08) | 0.18 (0.08) | 0.18 (0.09) | F = 0.60, P = .613 |
| % (n) | % (n) | % (n) | % (n) | ||
| Gender (% female) | 75.2 (708) | 89.0 (97) | 84.8 (89) | 80.7 (146) | X2 = 15.51, P = .001 0 < 1 |
| Self-reported ethnicity | X2 = 11.41, P = .249 | ||||
| White | 69.6 (649) | 61.7 (66) | 67.0 (69) | 76.4 (136) | |
| Asian or Pacific Islander | 13.2 (123) | 14.0 (15) | 13.6 (14) | 7.3 (13) | |
| Black | 6.6 (62) | 12.1 (13) | 7.8 (8) | 6.7 (12) | |
| Hispanic, Mixed, or Other | 10.6 (99) | 12.1 (13) | 11.7 (12) | 9.6 (17) | |
| Married or partnered (% yes) | 67.0 (623) | 62.6 (67) | 52.9 (54) | 58.9 (106) | X2 = 11.10, P = .011 0 > 2 |
| Lives alone (% yes) | 19.7 (183) | 17.6 (19) | 30.1 (31) | 28.5 (51) | X2 = 12.50, P = .006 0 < 3 |
| Currently employed (% yes) | 37.3 (348) | 30.6 (33) | 34.6 (36) | 26.7 (48) | X2 = 8.66, P =.034 0 > 3 |
| Annual household income | KW= 19.53, P <.001 0 > 2 and 3 |
||||
| Less than $30,000+ | 14.8 (125) | 28.9 (28) | 26.4 (24) | 26.1 (43) | |
| $30,000 to $70,000 | 21.2 (179) | 18.6 (18) | 24.2 (22) | 20.0 (33) | |
| $70,000 to $100,000 | 17.4 (147) | 14.4 (14) | 13.2 (12) | 18.2 (30) | |
| Greater than $100,000 | 46.6 (394) | 38.1 (37) | 36.3 (33) | 35.8 (59) | |
| Child care responsibilities (% yes) | 22.8 (211) | 22.9 (24) | 22.8 (23) | 18.2 (32) | X2 = 1.86, P = .602 |
| Elder care responsibilities (% yes) | 7.4 (64) | 7.4 (7) | 14.1 (14) | 7.0 (11) | X2 = 5.78, P = .123 |
| Past or current history of smoking (% yes) | 32.9 (306) | 37.0 (40) | 37.6 (38) | 45.5 (81) | X2 = 10.76, P =.013 0 < 3 |
| Level of exercise | X2 = 7.66, P = .264 | ||||
| Does not exercise on a regular basis | 35.1 (251) | 40.9 (36) | 39.2 (31) | 43.5 (64) | |
| Exercises less than 150 minutes per week | 45.1 (323) | 35.2 (31) | 44.3 (35) | 41.5 (61) | |
| Exercises 150 or more minutes per week | 19.8 (142) | 23.9 (21) | 16.5 (13) | 15.0 (22) | |
| Specific comorbid conditions (% yes) | |||||
| Heart disease | 5.1 (48) | 6.4 (7) | 3.8 (4) | 9.9 (18) | X2 = 7.45, P = .059 |
| High blood pressure | 30.1 (284) | 32.1 (35) | 25.7 (27) | 32.6 (59) | X2 = 1.68, P = .641 |
| Lung disease | 7.5 (71) | 14.7 (16) | 10.5 (11) | 29.3 (53) | X2 = 73.16, P <.001 0, 1, and 2 < 3 |
| Diabetes | 8.2 (77) | 15.6 (17) | 7.6 (8) | 10.5 (19) | X2 = 7.30, P= .063 |
| Ulcer or stomach disease | 4.5 (42) | 5.5 (6) | 4.8 (5) | 6.6 (12) | X2= 1.66, P = .645 |
| Kidney disease | 1.1 (10) | 1.8 (2) | 1.0 (1) | 3.3 (6) | X2 = 5.81, P = .121 |
| Liver disease | 6.0 (57) | 5.5 (6) | 9.5 (10) | 7.2 (13) | X2 = 2.23, P = .526 |
| Anemia or blood disease | 10.3 (97) | 19.3 (21) | 18.1 (19) | 14.9 (27) | X2 = 12.90, P= .005 0 < 1 |
| Depression | 15.4 (145) | 27.5 (30) | 22.9 (24) | 32.0 (58) | X2 = 33.90, P <.001 0 < 1 and 3 |
| Osteoarthritis | 10.4 (98) | 11.9 (13) | 16.2 (17) | 19.3 (35) | X2 = 13.07, P = .004 0 < 3 |
| Back pain | 22.2 (209) | 33.0 (36) | 31.4 (33) | 36.5 (66) | X2 = 22.02, P <.001 0 < 3 |
| Rheumatoid arthritis | 2.9 (27) | 1.8 (2) | 1.0 (1) | 7.2 (13) | X2 = 11.93, P = .008 0 < 3 |
| Cancer diagnosis | X2 = 76.19, P <.001 | ||||
| Breast cancer | 38.4 (362) | 51.4 (56) | 46.7 (49) | 39.8 (72) | NS |
| Gastrointestinal cancer | 35.4 (334) | 21.1 (23) | 21.0 (22) | 16.6 (30) | 0 > 1, 2, and 3 |
| Gynecological cancer | 17.7 (167) | 15.6 (17) | 18.1 (19) | 16.6 (30) | NS |
| Lung cancer | 8.5 (80) | 11.9 (13) | 14.3 (15) | 27.1 (49) | 0 and 1 < 3 |
| Co-occurrence of lung cancer and lung disease | 56.3 (45) | 61.5 (8) | 40.0 (6) | 79.6 (39) | X2 = 10.68, P = .014 0 and 2 < 3 |
| Prior cancer treatment | X2 = 26.42, P = .002 | ||||
| No prior treatment | 25.6 (235) | 19.8 (21) | 18.8 (19) | 28.2 (50) | NS |
| Only surgery, CTX, or RT | 43.6 (400) | 41.5 (44) | 46.5 (47) | 31.6 (56) | 0 > 3 |
| Surgery and CTX, or surgery and RT, or CTX and RT | 20.2 (185) | 20.8 (22) | 17.8 (18) | 18.6 (33) | NS |
| Surgery and CTX and RT | 10.6 (97) | 17.9 (19) | 16.8 (17) | 21.5 (38) | 0 < 3 |
| Receipt of targeted therapy (% yes) | 27.2 (251) | 33.3 (36) | 31.7 (33) | 40.9 (72) | X2 = 14.18, P = .003 0 < 3 |
| Cycle length | KW = 24.14, P <.001 0 < 3 |
||||
| 14 day cycleb | 45.5 (425) | 40.7 (44) | 41.0 (43) | 25.8 (46) | |
| 21 day cycle | 48.0 (449) | 52.8 (57) | 49.5 (52) | 63.5 (113) | |
| 28 day cycle | 6.5 (61) | 6.5 (7) | 9.5 (10) | 10.7 (19) | |
| Metastatic sites | X2 = 7.15, P = .622 | ||||
| No metastasis | 32.2 (299) | 34.0 (36) | 30.8 (32) | 33.3 (60) | |
| Only lymph node metastasis | 23.2 (216) | 17.9 (19) | 26.0 (27) | 16.1 (29) | |
| Only metastatic disease in other sites | 21.1 (196) | 20.8 (22) | 19.2 (20) | 22.8 (41) | |
| Metastatic disease in lymph nodes and other sites | 23.5 (219) | 27.4 (29) | 24.0 (25) | 27.8 (50) | |
| Lung metastasis (% yes) | 14.1 (89) | 21.1 (15) | 15.1 (11) | 30.0 (36) | X2 = 19.28, P <.001 0 < 3 |
| Emetogenicity of the CTX regimen | KW = 3.41, P = .332 | ||||
| Minimal/low | 18.1 (169) | 24.8 (27) | 19.0 (20) | 24.2 (43) | |
| Moderate | 63.2 (591) | 50.5 (55) | 56.2 (59) | 59.0 (105) | |
| High | 18.7 (175) | 24.8 (27) | 24.8 (26) | 16.9 (30) | |
| Antiemetic regimen and steroid NK-1 receptor antagonist and two other antiemetics | X2 = 4.02, P = .910 | ||||
| None | 7.2 (66) | 7.6 (8) | 5.9 (6) | 6.9 (12) | X2 = 4.02, P = .910 |
| Steroid alone or serotonin receptor antagonist lone | 19.5 (178) | 22.9 (24) | 23.5 (24) | 22.3 (39) | |
| Serotonin receptor antagonist and steroid | 49.0 (448) | 41.0 (43) | 46.1 (47) | 45.7 (80) | |
| NK-1 receptor antagonist and two other antiemetics | 24.3 (222) | 28.6 (30) | 24.5 (25) | 25.1 (44) | |
Abbreviations: CTX = chemotherapy, KW = Kruskal Wallis, NK-1 = neurokinin-1, NS = not significant, RT = radiation therapy, SD = standard deviation
Total number of metastatic sites evaluated was 9.
Reference group
In the total sample, compared to the None class, the Decreasing and High classes had lower hemoglobin levels, hematocrit levels, and red blood cell (RBC) counts (Table 3). In the males, compared to the None and Increasing classes, the Decreasing class had lower hemoglobin levels. In the males, compared to the other three classes, the Decreasing class had lower hematocrit levels. In the males, compared to the None and High classes, the Decreasing class had lower RBC counts. In females, compared to the None class, the High class had lower hemoglobin levels, hematocrit levels, and RBC counts.
Table 3.
Total Sample and Within Gender Differences in Red Blood Cell Counts, Hemoglobin Levels, and Hematocrit Levels Among the Shortness of Breath Latent Classes.
| Total Sample | |||||
|---|---|---|---|---|---|
| Blood test | None (0) 70.5% (n = 943) Mean (SD) |
Decreasing (1) 8.2% (n = 109) Mean (SD) |
Increasing (2) 7.8% (n = 105) Mean (SD) |
High (3) 13.5% (n = 181) Mean (SD) |
Statistics |
|
| |||||
| Hemoglobin (grams/deciliter) | 11.7 (1.4) | 11.0 (1.4) | 11.4 (1.4) | 11.3 (1.4) | KW = 24.50, P<.001 0 > 1 and 3 |
| Hematocrit (%) | 34.9 (4.1) | 33.1 (4.1) | 34.0 (4.1) | 33.8 (4.2) | KW = 26.09, P<.001 0 > 1 and 3 |
| RBC count (×106 microliters) | 3.9 (0.5) | 3.7 (0.6) | 3.7 (0.5) | 3.7 (0.6) | KW = 21.36, P<.001 0 > 1 and 3 |
| Males | |||||
| Blood test | None (0) | Decreasing (1) | Increasing (2) | High (3) | Statistics |
| 78.8% (n=234) | 4.0% (n=12) | 5.4% (n=16) | 11.8% (n=35) | ||
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | ||
| Hemoglobin (13.8 to 17.2 grams/deciliter) | 12.3 (1.6) | 10.3 (1.7) | 12.3 (1.3) | 11.9 (1.8) | KW = 13.71, P=.003 1 < 0 and 2 |
| Hematocrit (41% to 50%) | 36.8 (4.4) | 30.9 (4.4) | 36.6 (3.4) | 36.0 (5.5) | KW = 15.17, P=.002 1 < 0, 2, and 3 |
| RBC count (4.7 to 6.1 × 106 microliters) | 4.1 (0.6) | 3.3 (0.5) | 4.0 (0.4) | 4.0 (0.7) | KW = 16.63, P<.001 1 < 0 and 3 |
| Females | |||||
| Blood test | None (0) | Decreasing (1) | Increasing (2) | High (3) | Statistics |
| 68.1% (n=708) | 9.3% (n=97) | 8.6% | 14.0% (n=146) | ||
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | ||
| Hemoglobin (12.1 to 15.1 grams/deciliter) | 11.5 (1.3) | 11.1 (1.3) | 11.2 (1.4) | 11.1 (1.2) | KW= 11.63, P=.009 0 > 3 |
| Hematocrit (36% to 48%) | 34.3 (3.7) | 33.4 (4.0) | 33.6 (4.1) | 33.3 (3.7) | KW= 12.58, P=.006 0 > 3 |
| RBC count (4.2 to 5.4 × 106 microliters) | 3.8 (0.5) | 3.7 (0.6) | 3.7 (0.5) | 3.6 (0.5) | KW = 12.76, P=.005 0 > 3 |
Abbreviations: KW = Kruskal Wallis, RBC = red blood cell, SD = standard deviation Normal values for males and female are in parentheses
Frequency, Severity, and Distress of Shortness of Breath
For the patients who reported the occurrence of shortness of breath, significant differences were found among the classes in its frequency (P <.001; Fig. 2A). Post-hoc contrasts found that compared with the Decreasing class, High class reported a higher frequency of shortness of breath. In terms of severity (Fig. 2B), significant differences were found among the classes (p = .006). Post-hoc contrasts found that compared to the Increasing and Decreasing classes, High class had more severe shortness of breath. No differences in distress ratings for shortness of breath were found among the classes (Fig. 2C).
Fig. 2.
Percentages of patients in the decreasing, increasing, and high classes who rated the frequency (a), severity (b), and distress (c) associated with shortness of breath.
Co-occurrence of Other Respiratory Symptoms
Compared to the None class, other three classes reported higher occurrence rates for chest tightness and difficulty breathing (Table 4). Compared to the None class, Decreasing and High classes reported higher occurrence rates for cough. Compared to the Decreasing class, Increasing class reported a lower occurrence rate for difficulty breathing. Compared to the Increasing class, High class reported higher occurrence rates for difficulty breathing and cough.
Table 4.
Differences in the Occurrence of Respiratory Symptoms Among the Shortness of Breath Latent Classes.
| Symptom | None (0) 70.5% (n = 943) % (n) |
Decreasing (1) 8.2% (n = 109) % (n) |
Increasing (2) 7.9% (n = 105) % (n) |
High (3) 13.5% (n = 181) % (n) |
Statistics |
|---|---|---|---|---|---|
|
| |||||
| Chest tightness | 10.9 (102) | 42.2 (46) | 25.7 (27) | 34.6 (62) | X2 = 113.85, P <.001 0 < 1, 2, and 3 |
| Difficulty breathing | 7.5 (70) | 50.5 (55) | 24.8 (26) | 63.7 (114) | X2 = 370.77, P <.001 0 < 1, 2, and 3; 1 > 2; 2 < 3 |
| Cough | 26.5 (248) | 46.8 (51) | 36.2 (38) | 53.6 (96) | X2 = 62.53, P <.001 0 < 1 and 3; 2 < 3 |
QOL Scores
For the MQOLS-PV, compared to the None class, Decreasing and High classes had lower scores for psychological and social well-being, and total QOL (Table 5). Compared to the None class, other three classes had a lower physical well-being score. Compared to the Increasing class, High class had a lower spiritual well-being and total QOL scores.
Table 5.
Differences in Quality of Life Outcomes Among the Shortness of Breath Latent Classes.
| QOL outcomes | None (0) 70.5% (n = 943) Mean (SD) |
Decreasing (1) 8.2% (n = 109) Mean (SD) |
Increasing (2) 7.9% (n = 105) Mean (SD) |
High (3) 13.5% (n = 181) Mean (SD) |
Statistics |
|---|---|---|---|---|---|
|
| |||||
| Multidimensional quality of life scale – cancer | |||||
| Physical well-being | 6.9 (1.7) | 6.0 (1.8) | 6.4 (1.8) | 5.8 (1.8) | F = 23.05, P <.001 0 > 1, 2 and 3 |
| Psychological well-being | 5.7 (1.8) | 4.8 (1.8) | 5.4 (1.9) | 4.9 (1.8) | F = 15.58, P <.001 0 > 1 and 3 |
| Social well-being | 6.0 (2.0) | 5.0 (1.9) | 5.6 (2.0) | 5.0 (2.0) | F = 16.70, P <.001 0 > 1 and 3 |
| Spiritual well-being | 5.5 (2.1) | 5.6 (2.1) | 5.7 (2.0) | 5.0 (2.1) | F = 3.11, P = .026 2 > 3 |
| Total QOL score | 5.9 (1.4) | 5.2 (1.4) | 5.7 (1.4) | 5.1 (1.4) | F = 23.27, P <.001 0 > 1 and 3; 2 > 3 |
| Medical outcomes study short form – 12 (SF-12) | |||||
| Physical functioning | 58.0 (34.0) | 40.3 (31.8) | 48.0 (35.7) | 33.3 (27.7) | F= 33.01, P <.001 0 > 1, 2, and 3; 2 > 3 |
| Role physical | 56.0 (28.7) | 44.6 (28.7) | 48.6 (29.7) | 39.6 (28.7) | F = 19.56, P <.001 0 > 1 and 3 |
| Bodily pain | 79.1 (26.3) | 67.8 (32.6) | 72.8 (30.9) | 64.1 (30.9) | F = 17.82, P <.001 0 > 1 and 3 |
| General health | 66.2 (26.5) | 52.2 (29.2) | 59.9 (30.4) | 51.8 (29.2) | F = 19.78, P <.001 0 > 1 and 3 |
| Vitality | 48.6 (26.6) | 38.3 (26.5) | 41.7 (26.7) | 35.0 (25.3) | F = 16.76, P <.001 0 > 1 and 3 |
| Social functioning | 70.7 (29.2) | 58.6 (32.4) | 60.4 (31.8) | 56.4 (32.4) | F= 16.22, P <.001 0 > 1, 2, and 3 |
| Role emotional | 78.0 (26.6) | 69.2 (28.3) | 75.2 (26.3) | 67.6 (29.4) | F = 9.56, P <.001 0 > 1 and 3 |
| Mental health | 73.6 (19.8) | 65.0 (23.1) | 70.9 (22.5) | 67.7 (22.1) | F = 8.61, P <.001 0 > 1 and 3 |
| Physical component summary score | 43.0 (10.0) | 37.8 (10.4) | 39.5 (11.6) | 35.2 (10.2) | F= 32.32, P <.001 0 > 1, 2, and 3; 2 > 3 |
| Mental component summary score | 49.7 (10.1) | 46.6 (11.2) | 48.0 (10.2) | 47.1 (11.7) | F = 5.37, P = .001 0 > 1 and 3 |
Abbreviations: QOL = quality of life, SD = standard deviation
For the SF-12, compared to the None class, Decreasing and High classes had lower role physical, bodily pain, general health, vitality, role emotional, mental health, and MCS scores. Compared to the None class, other three classes had lower physical and social functioning and PCS scores. Compared to the Increasing class, High class had lower physical functioning and PCS scores.
Discussion
This study is the first to use LCA to identify subgroups of oncology patients with distinct shortness of breath profiles; evaluate its frequency, severity, and distress; describe the co-occurrence of other respiratory symptoms, and describe the impact of shortness of breath on QOL. Of note, across multiple types of cancer, approximately 30% of our patients reported shortness of breath. While our percentage is lower than the 44.4% reported in patients with advanced cancer receiving outpatient palliative care,6 these findings suggest that shortness of breath is a significant problem that warrants ongoing assessment and management in patients undergoing active treatment.
For the three classes who reported shortness of breath, the patterns of change in its occurrence were distinct. Of note, the High class had persistently high occurrence rates of shortness of breath for almost two months. In addition, for a larger percentage of patients in this class, their episodes of shortness of breath were more frequent and more severe. In terms of the Decreasing class, while detailed information is not available, a plausible hypothesis for this class’ trajectory is that they received effective interventions that decreased their shortness of breath (see below). In terms of the Increasing class, while specific data are not available, the increase in the occurrence rate of shortness of breath may be related to pulmonary toxicities associated with chemotherapy;7 lack of efficacy of the current treatment; and/or worsening of other chronic conditions.
One of the goals of this study was to identify common and distinct risk factors for shortness of breath among the latent classes (Table 6). The remainder of the discussion places our findings in the context of the extant literature.
Table 6.
Characteristics Associated with Membership in the Decreasing, Increasing, and High Shortness of Breath Classes.
| Characteristica | Decreasing | Increasing | High |
|---|---|---|---|
|
| |||
| Demographic characteristics | |||
| More likely to be older | ☐ | ||
| More likely to be female | ☐ | ||
| Less likely to be married/partnered | ☐ | ||
| More likely to live alone | ☐ | ||
| Less likely to be employed | ☐ | ||
| More likely to have a lower annual income | ☐ | ☐ | |
| Clinical characteristics | |||
| More likely to have past or current history of smoking | ☐ | ||
| Lower functional status | ☐ | ☐ | |
| Higher number of comorbidities | ☐ | ☐ | |
| Higher comorbidity burden | ☐ | ☐ | |
| More likely to self-report lung disease | ☐ | ||
| More likely to self-report anemia | ☐ | ||
| More likely to self-report depression | ☐ | ☐ | |
| More likely to self-report osteoarthritis | ☐ | ||
| More likely to self-report back pain | ☐ | ||
| More likely to self-report rheumatoid arthritis | ☐ | ||
| Less likely to have gastrointestinal cancer | ☐ | ☐ | ☐ |
| More likely to have lung cancer | ☐ | ||
| More likely to have lung metastasis | ☐ | ||
| More likely to have co-occurrence of lung cancer and lung disease | ☐ | ||
| Higher number of cancer treatments | ☐ | ||
| Less likely to have received only surgery, CTX, or RT | ☐ | ||
| More likely to have received all of the following treatments surgery, radiation, and CTX | ☐ | ||
| More likely to be receiving targeted therapy | ☐ | ||
| More likely to be receiving CTX on a 21- or 28-day cycle | ☐ | ||
| Co-occurrence of respiratory symptoms | |||
| More likely to have chest tightness | ☐ | ☐ | ☐ |
| More likely to have difficulty breathing | ☐ | ☐ | ☐ |
| More likely to have cough | ☐ | ☐ | |
| QOL outcomes | |||
| Multidimensional QOL scale – patient version | |||
| Lower physical well-being | ☐ | ☐ | ☐ |
| Lower psychological well-being | ☐ | ☐ | |
| Lower social well-being | ☐ | ☐ | |
| Lower total QOL score | ☐ | ☐ | |
| Medical outcomes study – short form 12 | |||
| Lower physical functioning | ☐ | ☐ | ☐ |
| Lower role physical | ☐ | ☐ | |
| Lower bodily pain | ☐ | ☐ | |
| Lower general health | ☐ | ☐ | |
| Lower vitality | ☐ | ☐ | |
| Lower social functioning | ☐ | ☐ | ☐ |
| Lower role emotional | ☐ | ☐ | |
| Lower mental health | ☐ | ☐ | |
| Physical component summary score | ☐ | ☐ | ☐ |
| Mental component summary score | ☐ | ☐ | |
☐ – indicates that the class had this characteristic compared to the None class
Abbreviations: CTX = chemotherapy, RBC = red blood cell, RT = radiation therapy, QOL = quality of life
Comparisons done with the None group
Demographic Characteristics
While not identified as a risk factor in previous studies,3,10,11 compared to the None class, Increasing and High classes were more likely to report a lower annual household income. In addition, the High class was more likely to be unemployed. Persistent shortness of breath may interfere with one’s ability to work or remain employed.2,12 These socioeconomic factors may contribute to a delay in seeking care and receiving timely symptom management interventions for shortness of breath.
While not modifiable, older age was a risk factor for being in the High class. Our finding is consistent with a previous study that noted that 30% of older adults reported shortness of breath despite the absence of cardiopulmonary comorbidities, obesity, or renal impairment.30 In our sample, this association may be related to vertebral deformities, as well as decreases in lung elasticity and respiratory muscle strength that occur with aging.31
Clinical Characteristics
Compared to the None class, Decreasing and High classes were more likely to have a higher number of comorbidities, a higher comorbidity burden, and a poorer functional status. In terms of specific comorbidities, in both of these classes, over 25% of the patients self-reported a diagnosis of depression. This finding is consistent with two studies of patients with lung cancer that used latent variable modeling to create subgroups of patients with distinct profiles using ratings of function32 and illness perceptions.33 In both studies, patients with the worst profiles reported higher rates of shortness of breath and depressive symptoms. Equally important, in a study that evaluated the efficacy of antidepressants in patients with advanced cancer,34 both depression and dyspnea scores decreased over time.
In addition, the High class reported higher rates of osteoarthritis, rheumatoid arthritis, and back pain. Our finding is consistent with a study of community-dwelling older adults that found that individuals with shortness of breath were more likely to experience the co-occurrence of back pain and arthritis pain.35 One potential explanation for this finding is that pain associated with activity or movement may exacerbate patients’ experiences of shortness of breath. These findings suggest patients who report shortness of breath need to be evaluated for depression and pain and have appropriate interventions prescribed.
Consistent with previous studies,3,10 a larger percentage of patients in the High class were past or current smokers, self-reported lung disease, and had primary or metastatic lung cancer. These risk factors are not surprising given that 56.7% of lung cancer patients at the time of diagnosis10 and 95% of patients with chronic obstructive pulmonary disease8 report shortness of breath. In addition, it is well documented that smoking causes or worsens lung disease and lung cancer36 and that preexisting lung diseases are associated with an increased risk of lung cancer.37 Equally important, the co-occurrence of respiratory disease and lung cancer increases the risk of developing drug-induced pulmonary toxicity.7
A large number of treatment factors were associated with membership in the High class. Overall, this class was more likely to have received multiple types of cancer treatment and were more likely to be receiving targeted therapy. For the patients in this class who had breast or lung cancer, the receipt of thoracic surgery and/or thoracic or whole breast radiotherapy may damage lung tissue, create scar tissue, and result in pulmonary fibrosis.38,39 In addition, the administration of platinum- and/or taxane-containing regimens, that are routinely used to treat lung, breast, gastric, and gynecologic cancers, are associated with pulmonary toxicity.7,40 In terms of targeted therapy, of the 392 patients in the total sample who received targeted therapy, 46.2% (n=181) of them were in the High class. While a detailed analysis of associations between shortness of breath and specific targeted therapies cannot be performed due to the wide variety of agents administered, additional research is warranted to evaluate for differences in the occurrence and severity of this symptom in patients who do and do not receive these agents.
Compared to the None class, a higher percentage of patients in Decreasing class reported anemia. In addition, the male patients in this class had lower hemoglobin levels, hematocrit levels, and RBC counts. This shortness of breath trajectory is somewhat surprising because this symptom is commonly reported by oncology patients with anemia. One potential explanation for the decreases in the occurrence of shortness of breath in Decreasing class is that these patients received blood transfusions with a resultant increase in the oxygen carrying capacity of the blood.
Co-occurring Respiratory Symptoms
Compared to the None class, the other three classes reported higher occurrence rates for chest tightness and difficulty breathing. While the exact etiology for chest tightness is unknown, 17.8% of our total sample of patients with heterogeneous types of cancer reported its occurrence. Our finding is supported by a study of patients with advanced cancer and COPD,13 that found that chest tightness was reported only by the oncology patients.
In terms of difficulty breathing, 19.9% of the total sample reported this symptom at enrollment which is lower than the occurrence rate for shortness of breath (i.e., 26.9% of the total sample at enrollment). While the literature suggests that these two symptoms are distinct,13,15 additional research is warranted to determine how patients interpret these two descriptors and whether the risk factors for and mechanisms that underlie these two symptoms are similar. Potential etiologies for the co-occurrence of chest tightness and difficulty breathing with shortness of breath include ongoing irritation of pulmonary afferents from the cancer itself, airway inflammation, and/or a pleural effusion.15
While the overall occurrence rate for cough in the total sample was 32.6% at enrollment, compared with the None class, these rates were higher in the Decreasing and High classes. Our finding is consistent with previous studies that found that 35.1% to 42.9% of oncology outpatients receiving active treatment reported cough.41,42 While the exact etiologies for cough are not well understood, they may include: activation of bronchopulmonary C-fibers by the cancer itself, a pleural effusion, and/or toxicities of cancer treatments.43 Given the relatively high co-occurrence rates for all four symptoms, they should be routinely assessed as a “bundle” in patients who report any singular symptom.
QOL Outcomes
It should be noted that for the SF-12, all four classes reported PCS and MCS scores of <50, which is normative score for the general population of the United States.44 Compared to the None class, both the Decreasing and High classes reported worse scores for the QOL domains of physical, psychological, and social functioning on both the generic and cancer-specific measures. Our findings are consistent with a study of patients with lung cancer who were scheduled for chemotherapy that reported that shortness of breath resulted in significant impairments in daily activities.45 In addition, shortness of breath may deter patients from participating in social activities which can increase feelings of social isolation.2
Limitations
Several limitations warrant consideration. Given that our sample was relatively homogenous in terms of gender and ethnicity, our findings may not generalize to more diverse ethnic groups. While this study used a valid and reliable measure to assess the subjective experience of shortness of breath, future studies need to evaluate for correlations with objective measures of pulmonary function. In addition, detailed information is needed on the patients’ specific cardiopulmonary conditions. Finally, information on pharmacologic and nonpharmacologic treatments for shortness of breath were not available for our sample.
Conclusions
Despite these limitations, this study provides new information on the occurrence severity, distress, and risk factors for shortness of breath, co-occurring respiratory symptoms, and QOL outcomes in a sample of patients with heterogeneous types of cancer. In addition, a number of modifiable risk factors (e.g., poorer physical functioning, anemia, depression) were identified. It should be noted that in two studies that evaluated the efficacy of pulmonary rehabilitation to improve physical functioning, shortness of breath, and QOL in patients with lung cancer receiving chemotherapy,46,47 receipt of the intervention resulted in decreases in symptom severity and improvements in physical function. Given the positive results in these studies, oncology clinicians can recommend this type of program to patients with shortness of breath.
Key Message.
This study is the first to identify subgroups of patients with heterogenous types of cancer with distinct shortness of breath profiles. Regardless of type of cancer, 30% of patients receiving chemotherapy reported shortness of breath.
Disclosure and Acknowledgments
This study was funded by a grant from the National Cancer Institute (CA134900). Ms. Shin is supported by a University of California, San Francisco, School of Nursing fellowship and research grants from Sigma Theta Tau International Alpha Eta Chapter and Oncology Nursing Foundation. Dr. Wong is supported by a grant from the National Institute on Aging (K76AG064431). Dr. Miaskowski is an American Cancer Society Clinical Research Professor. The study sponsors had no role in the study design, collection, analysis, interpretation of data, writing the report, or the decision to submit the information for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Wong reported conflicts of interest outside of the submitted work: An immediate family member is an employee of Genentech with stock ownership and Dr. Wong receives royalties from UpToDate. The remaining authors have no conflicts of interest to declare.
Contributor Information
Joosun Shin, School of Nursing, University of California, San Francisco, California, USA.
Kord M. Kober, School of Nursing, University of California, San Francisco, California, USA.
Melisa L. Wong, School of Medicine, University of California, San Francisco, California, USA.
Patsy Yates, Cancer & Palliative Outcomes Centre, Centre for Health Transformation, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.
Bruce A. Cooper, School of Nursing, University of California, San Francisco, California, USA.
Steven M. Paul, School of Nursing, University of California, San Francisco, California, USA.
Marilyn Hammer, Dana Farber Cancer Institute, Boston, Massachusetts, USA.
Yvette Conley, School of Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Jon D. Levine, School of Medicine, University of California, San Francisco, California, USA.
Christine Miaskowski, School of Nursing, University of California, San Francisco, California, USA; School of Medicine, University of California, San Francisco, California, USA.
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