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. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: J Pain Symptom Manage. 2020 Jul 25;61(1):24–31.e4. doi: 10.1016/j.jpainsymman.2020.07.019

Higher Levels of Stress Are Associated with a Significant Symptom Burden in Oncology Outpatients Receiving Chemotherapy

Katarina Jakovljevic 1, Kord M Kober 1, Astrid Block 1, Bruce A Cooper 1, Steven M Paul 1, Marilyn J Hammer 2, Frances Cartwright 3, Yvette P Conley 4, Fay Wright 5, Laura B Dunn 6, Jon D Levine 7, Christine Miaskowski 1
PMCID: PMC7770050  NIHMSID: NIHMS1615315  PMID: 32721501

Abstract

Context:

A cancer diagnosis and associated treatments, as well as the uncertainty of the disease course are stressful experiences for most patients. However, little information is available on the relationship between stress and symptom burden. Study purpose was to evaluate for differences in the severity of fatigue, lack of energy, sleep disturbance, and cognitive function, among three groups of patients with distinct stress profiles.

Methods:

Patients receiving chemotherapy (n=957) completed measures of general, cancer-specific, and cumulative life stress and symptom inventories. Latent profile analysis was used to identify subgroups of patients with distinct stress profiles.

Results:

Three distinct subgroups of patients were identified (i.e., Stressed (39.3%), Normative (54.3%), Resilient (5.7%)). For cognitive function, significant differences were found among the latent classes (Stressed<Normative<Resilient). For both sleep disturbance and morning and evening fatigue, compared to the Normative and Resilient classes, the Stressed class reported higher severity scores. Compared to the Normative and Resilient classes, the Stressed class reported low levels of morning energy. Compared to the Normative class, the Stressed class reported lower levels of evening energy.

Conclusions:

Consistent with our a priori hypothesis, patients in the Stressed class had the highest symptom severity scores for all four symptoms and all of these scores were above the clinically meaningful cutoffs for the various instruments.

Keywords: stress, cancer, chemotherapy, fatigue, sleep disturbance, cognitive dysfunction

INTRODUCTION

A cancer diagnosis, its related treatments, and the uncertainty of the disease course are stressful experiences for most patients.1,2 While the types and the duration of stressors, as well as their impact, vary greatly,3 a significant amount of variability in individuals’ cognitive, emotional, and neurobiological responses to stress.4 A growing, albeit limited, body of preclinical and clinical evidence, summarized below, suggests that these inter-individual differences in oncology patients’ responses to stress may contribute to the occurrence and severity of common physical symptoms (i.e., fatigue, sleep disturbance, deficits in energy levels, cognitive impairment) associated with the receipt of chemotherapy (CTX).

Fatigue occurs in up to 90% of patients undergoing CTX.5 In the general population, fatigue is an adaptive response to acute stress that assists an individual to conserve energy and maintain homeostasis. However, in situations of chronic stress or cumulative exposure to stressful life events, the sympathetic nervous system (SNS), parasympathetic nervous system (PNS), and hypothalamic-pituitary-adrenal (HPA) axis experience an increased allostatic load which results in increases in fatigue severity.6 In terms of oncology patients, as suggested in a recent review,2 stress-induced increases in inflammatory responses may be one of the underlying mechanisms for fatigue. However, only one study was identified that evaluated for associations between fatigue severity and stress in oncology patients receiving CTX. In this study, that used latent profile analysis (LPA) to identify subgroups of patients with distinct morning and evening fatigue profiles,7 higher levels of general and disease-specific stress were reported by patients in the highest morning and evening fatigue subgroups.

Sleep disturbance is reported by 30% to 88% of oncology patients and has a significant impact on patients’ mood, functional status, and quality of life.8,9 As noted in two recent reviews,10,11 findings from several animal and human studies suggest that stress can have an impact on the sleep-wake cycle in a variety of ways depending primarily on the types of stressors experienced, the duration of exposure (i.e., acute versus chronic stress), and inter-individual responses to stress. However, research on the association between sleep disturbance and stress in oncology patients in extremely limited. In the only study identified,12 that evaluated twenty-nine newly diagnosed patients with breast cancer and co-occurring insomnia, while no measure of stress was used, patients with insomnia prior to their cancer diagnosis reported high cognitive arousal scores (i.e., a proxy measure of stress) prior to bedtime.

Cancer-related cognitive impairment (CRCI) can occur in up to 75% of patients receiving CTX.13 In an excellent review,14 Datta and Arnsten described the influences of chronic stress on the functioning of the prefrontal cortex (PFC). Findings across studies of the general population suggest that this area of the brain, that controls behaviors, thoughts, and emotions, when exposed to chronic stress exhibits changes in connectivity and neuronal atrophy. It is interesting to note that in a recent magnetic resonance imaging (MRI) study of forty patients with breast cancer,15 CRCI was associated with changes in functional connectivity in the PFC. In addition, findings from a systematic review suggest that psychosocial factors, including increased stress, are associated with CRCI.16 Finally, in a study of patients undergoing CTX,17 higher levels of general and disease specific stress were associated with worst cognitive dysfunction.

Given the high levels of stress that oncology patients experience; the growing preclinical evidence, as well as evidence from the general population, on the associations between stress and common physical symptoms; and the paucity of research on these associations in oncology patients, in this study we extend our work on stress in oncology patients. This current analysis study is an extension of our previous report that identified distinct stress profiles in a large sample of oncology patients undergoing CTX (n=957).18 In brief, we used LPA to identify subgroups of patients based on their concurrent evaluations of global (i.e. Perceived Stress Scale19) and cancer-specific stress (i.e., Impact of Event Scale-Revised20), lifetime stress exposure (i.e., Life Stressor Checklist-Revised21), and resilience (i.e., Connor-Davidson Resilience Scale22). Three subgroups of patients with distinct stress profiles were identified (Table 1). The first group, labeled “Stressed” (39.3%) reported the highest levels of global and cancer specific stress, the lowest resilience scores, and the most life stress. The second group, labeled “Normative” (54.3%), was characterized by intermediate levels of global stress and resilience, lower levels of cancer-related stress, and the lowest amount of cumulative life stress. The third group, labeled “Resilient” (5.7%) had the lowest global stress scores, levels of cancer-specific stress that were comparable to the “normative” group, the highest resilience scores, and intermediate levels of cumulative life stress. The purpose of this study was to evaluate for differences in the severity of fatigue, lack of energy, sleep disturbance, and cognitive function, among these three stress groups. We hypothesized that compared to patients in the other two groups, patients in the “stressed” group would have the highest physical symptom severity scores.

Table 1 –

Differences Among the Latent Classes in the Stress Profile Measures1

Characteristic Stressed (1) 39.9% (n = 382) Normative (2) 54.3% (n = 520) Resilient (3) 5.7% (n = 55) Statistics
Mean (SD) Mean (SD) Mean (SD)
Perceived Stress Scale 25.4 (6.7) 14.2 (5.0) 8.5 (4.5) F=502.26, p<.001 1>2>3
Impact of Event Scale-Revised (IES-R) total score 27.9 (13.8) 12.0 (7.0) 15.4 (12.1) F=244.85, p<.001 1>2 and 3
Life Stressor Checklist-Revised (LSC-R) total score 8.0 (4.7) 4.6 (2.4) 6.2 (4.2) F=92.34, p<.001 1>3>2
Connor Davidson Resilience score 25.7 (6.4) 32.2 (4.2) 39.7 (0.5) F=276.40, p<.001 1<2<3

Abbreviation: SD = standard deviation

1

Reprinted with permission from Langford DJ, Cooper B, Paul S, Humphreys J, Hammer MJ, Levine J, Conley YP, Wright F, Dunn LB, Miaskowski C. Distinct stress profiles among oncology patients undergoing chemotherapy. J Pain Symptom Manage. 2020; 59(3):646–657.

METHODS

Patients and Settings

This analysis used data from a descriptive, longitudinal study that evaluated the symptom experience of oncology outpatients receiving CTX.23 Eligibility criteria included: ≥18 years of age; diagnosis of breast, gastrointestinal, gynecological, or lung cancer; received CTX within the preceding four weeks and scheduled to receive two additional cycles; and able to read, write, and understand English. Recruitment occurred at two Comprehensive Cancer Centers, one Veteran’s Affairs hospital, and four community-based oncology clinics. Written informed consent was obtained from all patients. Study procedures were approved by the Committee on Human Research at the University of California, San Francisco and by each study site. Of the 2234 patients approached, 1343 consented to participate (60.1%). Patients who completed all of the stress and resilience measures (n=957) were included in this analysis.

Instruments

Demographic and Clinical Characteristics

Patients completed a demographic questionnaire, the Karnofsky Performance Status (KPS) scale,24 and the Self-Administered Comorbidity Questionnaire (SCQ).25 Medical records were reviewed for disease and treatment information.

Stress and Resilience Measures

Perceived Stress Scale (PSS) –

The 14-item PSS was used to assess global stress.19 Patients indicated the degree to which they perceived life circumstances as stressful over the previous week. Items were rated from 0 (never) to 4 (very often). Higher sum scores indicate greater perceived stress. The PSS has well established validity and reliability.19 In this current study, its Cronbach’s alpha was 0.89.

Impact of Event Scale-Revised (IES-R) –

The IES-R is a 22-item instrument that was used to measure distress associated with cancer and its treatment.20 Patients rated each item based on how distressing each potential difficulty was for them during the past week “with respect to their cancer and its treatment”. Each item was rated on a 0 to 4 Likert scale (i.e., 0 = not at all, 1 = a little bit, 2 = moderately, 3 = quite a bit, 4 = extremely). Three subscales were created using the mean of the responses. A total IES-R score was created by summing the responses to the 22 items. The three subscales evaluate the levels of intrusion, avoidance, and hyperarousal perceived by a patient. The total IES-R score can range from 0 to 88. For the total IES-R score, a sum score of ≥24 indicates clinically meaningful post-traumatic symptomatology and scores of ≥33 indicate probable PTSD.26,27 The IES-R has well established validity and reliability.26 In the current study, its Cronbach’s alpha was 0.92.

Life Stressor Checklist-Revised (LSC-R) –

The 30-item LSC-R was used to evaluate lifetime exposure to stressful life events.21 Patients indicated the occurrence of 30 stressors and rated the effect of each stressor on their past year of life, from 1 (not at all) to 5 (extremely). A higher number (i.e., count) of stressful life events and higher mean effect scores indicate greater stress exposure and impact, respectively. LSC-R demonstrates adequate test–retest reliability and criterion-related validity among diverse populations.28,29

Connor-Davidson Resilience Scale (CD-RISC-10) –

The 10-item CD-RISC-10 was used to measure resilience.22 Items were rated from 0 (not true at all) to 4 (true nearly all the time). Higher sum scores indicate greater resilience. CD-RISC-10 has adequate validity and reliability in diverse populations.22,30 In the current study, its Cronbach’s alpha was 0.90.

Symptom Measures

Attentional Function Index (AFI) –

The 16-item AFI was designed to measure attentional function.31 A higher total mean score on a 0 to 10 NRS indicates greater capacity to direct attention.31 Total scores are grouped into categories of attentional function (i.e., <5.0 low function, 5.0 to 7.5 moderate function, >7.5 high function).32 In addition, the AFI has three subscales (i.e., effective action, attentional lapses, interpersonal effectiveness). The AFI has well established reliability and validity.31 In this study, the Cronbach’s alpha for the total AFI score was 0.93.

General Sleep Disturbance Scale (GSDS) –

The 21-item GSDS was designed to assess the quality of sleep in the past week.33 Each item was rated on a 0 (never) to 7 (everyday) NRS. The GSDS total score is the sum of the seven subscale scores that can range from 0 (no disturbance) to 147 (extreme sleep disturbance). Each mean subscale score can range from 0 to 7. Higher total and subscale scores indicate higher levels of sleep disturbance. Subscales scores of ≥3 and a GSDS total score of ≥43 indicate a significant level of sleep disturbance.34 The GSDS has well-established validity and reliability.33,35,36 In the current study, the Cronbach’s alpha for the GSDS total score was 0.83.

Lee Fatigue Scale (LFS) –

The 18-item LFS is designed to assess physical fatigue and energy.37 Each item was rated on a 0 to 10 numeric rating scale (NRS). Total fatigue and energy scores are calculated as the mean of the 13 fatigue items and the 5 energy items, respectively. Higher scores indicate greater fatigue severity and higher levels of energy. Using separate LFS questionnaires, patients were asked to rate each item based on how they felt within 30 minutes of awakening (i.e., morning fatigue, morning energy) and prior to going to bed (i.e., evening fatigue, evening energy). The LFS has established cut-off scores for clinically meaningful levels of fatigue (i.e., ≥3.2 for morning fatigue, ≥5.6 for evening fatigue)34 and energy (i.e., ≤6.2 for morning energy, ≤3.5 for evening energy).34 It was chosen for this study because it is relatively short, easy to administer, and has well established validity and reliability.3641 In the current study, the Cronbach’s alphas were 0.96 for morning and 0.93 for evening fatigue and 0.95 for morning and 0.93 for evening energy.

Data Analysis

As described previously,18 LPA was used to identify subgroups (i.e., latent classes) of patients with distinct stress profiles, using patients’ scores on the stress (PSS, IES-R, LSC-R) and resilience (CD-RISC-10) measures. LPA was conducted using MPlus™ Version 7.4.42 Estimation was conducted using robust maximum likelihood and the expectation maximization algorithm. Statistical fit indices were used to determine the number of classes that best captured variability, while maintaining conceptual clarity.43,44

Descriptive statistics and frequency distributions were calculated for demographic and clinical characteristics, stress and resilience scores, using SPSS version 26.45 Analyses of variance, Kruskal-Wallis, or Chi-square analyses were used to evaluate for differences in demographic and clinical characteristics and symptom scores among the classes. A p-value of <0.05 were considered statistically significant. The Bonferroni correction was used for post hoc contrasts.

RESULTS

Results of the LPA

The LPA identified three latent classes based on the stress and resilience measures.18 Supplemental Table 1 displays the fit indices for the 1- through 4-class solutions. The 3-class solution was selected based on its lower Bayesian Information Criterion, higher entropy, and statistically significant Vuong-Lo-Mendell-Rubin, indicating the best fit.

As noted in our previous publication,18 of the entire sample, 382 patients (39.9%) were classified as “Stressed”, 520 patients (54.3%) as “Normative”, and 55 patients (5.7%) as “Resilient”. To name these classes (Table 1), mean stress and resilience scores were compared among the classes, as well as to established cut-off scores26 and national normative data.22,46 The latent classes differed significantly on all of the stress and resilience scores (all p<0.001). Post hoc contrasts revealed consistent patterns for global stress (i.e., PSS; Stressed > Normative > Resilient) and resilience (Stressed < Normative < Resilient). For occurrence of life stressors measured using the LSC-R, post hoc contrasts revealed the following pattern: Stressed > Resilient > Normative. For cancer-related stress, Stressed patients reported higher IES-R total scores than Normative and Resilient patients (i.e., Stressed > Normative and Resilient).18

Differences in Demographic and Clinical Characteristics

As noted in our previous publication,18 compared to Normative patients, Stressed patients were younger, more likely to be female, had fewer years of education, lower annual household incomes, and were less likely to be employed. Compared to Normative and Resilient classes, Stressed patients were more likely to be single and live alone (Supplemental Table 2).

For clinical characteristics, functional status, comorbidities, as well as self-reported depression and back pain differed among the latent classes. Compared to Normative patients, Stressed patients reported a higher comorbidity burden and were more likely to report back pain. Compared to Normative and Resilient patients, Stressed patients had lower functional status scores and were more likely to report depression. Demographic and clinical characteristics did not differ between Normative and Resilient patients. Moreover, no disease or treatment characteristics differed among the classes.

Differences in Symptom Severity Scores

As shown in Table 2, for attentional function, significant differences in the interpersonal effectiveness and total AFI scores were found among the latent classes (Stressed < Normative < Resilient). In addition, compared to the other two classes, patients in the stressed class had lower effective action and attentional lapses subscale scores.

Table 2 –

Differences in Symptom Characteristics Among the Stress Latent Classes

Symptom scores Clinically Meaningful Cutoff Scores Stressed (1) 39.9% (n = 382) Normative (2) 54.3% (n = 520) Resilient (3) 5.7% (n = 55) Statistics
Mean (SD) Mean (SD) Mean (SD)
Attentional function total score <5.0 – low 5 to 7.5 – moderate 7.5–high 5.4(1.6) 7.0 (1.6) 7.7 (1.5) F = 135.70, p<.001 1 < 2 < 3
 Effective action subscale n/a 5.1 (1.9) 6.8 (2.0) 7.4 (1.9) F = 95.75, p<.001 1 < 2 and 3
 Attentional lapses subscale n/a 5.6 (2.0) 7.2 (1.8) 7.6 (2.0) F = 15.87, p<.001 1 < 2 and 3
 Interpersonal effectiveness subscale n/a 5.8 (2.0) 7.4 (1.7) 8.4 (1.3) F = 103.56, p<.001 1 < 2 < 3
Sleep disturbance total score ≥43 61.4 (19.6) 45.6 (18.1) 48.4 (21.6) F = 75.58, p<.001 1 > 2 and 3
 Quantity of sleep ≥3 3.9 (1.7) 2.9 (1.7) 3.1 (1.7) F = 43.75, p<.001 1 > 2 and 3
 Quality of sleep ≥3 4.7 (1.7) 4.6 (1.4) 4.6 (1.6) F = 1.14, p = .320
 Sleep onset latency ≥3 3.6 (2.3) 2.2 (2.1) 2.2 (2.3) F = 49.50, p<.001 1 > 2 and 3
 Mid-sleep awakenings ≥3 5.2 (2.1) 4.7 (2.3) 4.7 (2.3) F = 5.45, p = .004 1 >2
 Early awakenings ≥3 4.3 (2.4) 3.0 (2.4) 3.2 (2.8) F = 30.18, p<.001 1 > 2 and 3
 Excessive daytime sleepiness ≥3 3.2 (1.4) 2.1 (1.3) 2.4 (1.5) F = 63.15, p<.001 1 > 2 and 3
 Medications for sleep ≥3 0.8 (0.9) 0.5 (0.7) 0.5 (0.8) F = 22.49, p < .001 1 > 2 and 3
Morning fatigue ≥3.2 4.1 (2.4) 2.4 (1.9) 2.4 (2.0) F = 73.21, p<.001 1 > 2 and 3
Evening fatigue ≥5.6 5.8 (2.1) 5.0 (2.0) 4.5 (2.3) F = 18.37, p<.001 1 > 2 and 3
Morning energy ≤6.2 3.9 (2.1) 4.7 (2.2) 4.9 (2.5) F = 18.62, p<.001 1 < 2 and 3
Evening energy ≤3.5 3.2 (2.0) 3.8 (1.9) 3.9 (2.3) F = 9.24, p < .001 1 <2

Abbreviations: NS = not significant, SD = standard deviation

For sleep disturbance, as well as morning and evening fatigue, compared to the Normative and Resilient classes, patients in the Stressed class reported higher GSDS and LFS scores. For morning energy, compared to the Normative and Resilient classes, patients in the Stressed class reported low scores. For evening energy, compared to the Normative class, patients in the Stressed class reported lower scores.

DISCUSSION

This study is the first to evaluate for differences in fatigue, energy levels, sleep disturbance, and cognitive function in subgroups of patients with distinct stress profiles. Details on the differences among these subgroups in terms of their specific stress profiles, as well as demographic and clinical characteristics are described in our previous publication,18 which allows us to focus this discussion our findings related to differences among the subgroups in the severity of common physical symptoms associated with cancer and CTX administration.

Consistent with our a priori hypothesis, patients in the Stressed class had the highest symptom severity scores for all four symptoms and all of these scores were above the clinically meaningful cutoffs for the various instruments. In contrast, while the stress and resilience scores differed between the Normative and Resilient classes, for most of the symptoms, no between group differences in symptom severity scores were found. This finding may be related to the relatively high symptom burden experienced by all three classes or the relatively small number of patients in the Resilient class. An additional consideration may be that the correlations between the various symptom scores differed among the latent classes. As shown in Supplemental Table 3, the correlations between the various symptoms were in the small to moderate range and did not differ among the latent classes.

While numerous studies have investigated risk factors for CRCI,4750 the majority evaluated for associations with only demographic, clinical, and treatment characteristics. In this study, we provide additional evidence that a subgroup of oncology patients with high levels of general and disease-specific stress, as well as cumulative life stress had the worse decrements in cognitive function. While the total scores and the interpersonal effectiveness subscale scores of the AFI differentiated among the three classes, both the Stressed and Normative classes had total AFI scores that suggest moderate decrements in cognitive function. As a subjective measure, the AFI evaluates patients’ perceptions of their effectiveness in carrying out basic activities of daily living that require focused attention; their perceived difficulties in directing attention on daily tasks, as well as their perceptions of their ability to interact in a deliberate manner that depends on selective attention.31 While controversy exists on whether subjective and/or objective measures should be used to evaluate CRCI, in a recent functional MRI study, that evaluated patients with breast cancer undergoing CTX,51 decreases in AFI scores paralleled disruptions in resting-state blood oxygen level dependent (BOLD) functional connectivity in parietal and frontal brain regions. To confirm the previous observations that chronic stress effects the functioning of the PFC,14 future studies of CRCI should include both subjective and objective measures of cognitive function as well as multidimensional measures of stress.

While all three latent classes reported total sleep disturbance scores above the clinically meaningful cutoff, patients in the Stressed class had scores that represent an extremely high level of sleep disturbance that is comparable to scores reported by shift workers (i.e., 60.5)33 and parents of newborn infants (55.5).38 In terms of the GSDS subscale scores, the high levels of mid-sleep and early awakenings suggest that all three classes have problems with sleep maintenance. Of note, for patients in the Stressed class, all of the GSDS subscale scores were above the clinically meaningful cutoff of >3 days per week. In particular, their score of 3.6 (+2.3) on the sleep onset latency subscale suggests that these patients have problems with both sleep initiation and maintenance. Our findings are consistent with the preclinical and human studies of the negative impact of stress on sleep.10,11

Previous research from our group demonstrated that morning and evening fatigue are distinct but related symptoms.23,52,53 Based on the scores reported by our Stressed class, high levels of general and disease specific stress, as well as cumulative life stress are associated with clinically meaningful levels of both morning and evening fatigue. While lack of energy and fatigue are used interchangeably in the symptom literature, a growing body of evidence suggests that energy and fatigue are distinct but related symptoms.5456 While no studies have evaluated for associations between decrements in energy levels and stress, our Stressed class reported clinically meaningful decrements in both morning and evening energy levels and the other two classes reported morning energy levels that were well below the clinically meaningful cutoff of ≤6.2. These findings may be related to the relatively high levels of sleep disturbance in all three classes and warrant confirmation in future studies.

Consistent with our a priori hypothesis, patients in the Stressed class reported the highest level of symptom burden. Of note, the patients in this subgroup (i.e., 40% of the sample) reported clinically meaningful levels of all four of these co-occurring symptom. This extremely high risk group was younger, more likely to be female, had a lower socioeconomic status, was not married or partnered, was more likely to live alone, had a poorer functional status, and a worse comorbidity profile (see Supplementary Table 2).18 These high risk patients warrant ongoing assessments of both stress and symptom burden.

While this study has several limitations, it provides directions for future research. While the sample was heterogeneous in terms of cancer types and CTX regimens, it was fairly homogenous in terms of gender, educational level, and ethnicity. In addition, this study focused on associations between stress and physical symptoms in oncology patients, future studies need to examine the relationships between stress profiles and anxiety and depressive symptoms. Given that the stress measures were done only once, changes in the severity of stress and symptoms could not be evaluated. Future longitudinal studies, that use analytic techniques like parallel process growth modeling,57 will be able to discern the causal relationships between stress and symptom burden. While recent investigations in symptoms science are focused on an evaluation of multiple co-occurring symptoms and symptom clusters in oncology patients and patients with other chronic conditions,58,59 as noted in the introduction to this paper, the limited amount of research has focused on an examination of the relationships between stress and single symptoms. Given the findings from this study, careful consideration should be given to an evaluation of not only general, disease-specific, and cumulative life stress but multiple co-occurring symptoms in patients with cancer and other chronic conditions. These types of studies that include both subjective and objective measures, as well as biomarkers will increase our knowledge of the fundamental mechanisms that underlie the relationships between stress and symptoms.

Supplementary Material

1

Acknowledgments

Disclosures: This study funded by the National Cancer Institute (NCI, CA134900). Dr. Miaskowski is an American Cancer Society Clinical Research Professor. Ms. Jakovljevic’s education was supported by the University of California, San Francisco Nursing Award, Will and Jacquelyn Tobias Foundation Scholarship, Nancy Tempkin Memorial Scholarship, Ronald and Ann Williams Scholarship, and Kaiser Permanente Deloras Jones Scholarship.

Footnotes

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Conflict of interest: The authors have not conflicts of interest to declare.

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