EXPERIMENTAL AND CLINICAL TRANSPLANTATION

Objectives: Health-related quality of life has been well studied across transplantation fields, but factors associated with lung transplant preoperative and postoperative quality of life remain unknown. Here, we determine factors associated with health-related quality of life in lung transplant candidates and recipients to identify patients at risk of lower health-related quality of life.

Materials and Methods: From January 2021 to May 2022, health-related quality of life was measured in candidates and recipients using the RAND 36-Item Short Form Health Survey questionnaire. We reviewed demographic parameters and clinical information and scored frailty according to the modified 5-item frailty index. We performed Fisher exact test and the Pearson chi-square test and used linear regression models to determine covariate associations on physical component summary, mental component summary, and self-reported health scores (α = 0.05).

Results: Eleven candidates and 17 recipients comp-leted the survey. Compared with candidates, transplant recipients reported significantly higher scores in 4 of the 8 health domains and in the physical component summary (P < .01), mental component summary (P = .05), and self-reported health score (P < .01). In candidates, higher body mass index and higher modified 5-item frailty index scores were negatively associated with the physical component summary and mental component summary, respec-tively (P < .05). In recipients, higher body mass index and higher lung allocation scores were associated with lower values for the physical component summary (-2.29; P < .05) and self-reported health score (-0.33; P < .05), respectively.

Conclusions: Body mass index, the modified 5-item frailty index, and the lung allocation score were significantly associated with health-related quality of life in lung transplant recipients. Future interventions should target these modifiable associations to maximize candidate and recipient health-related quality of life.

Key words : Frailty index score, Lung allocation score, Lung transplantation, Solid-organ transplant, Transplant waitlist

Solid-organ transplant can prolong the life of patients facing end-organ failure.1 Measurement of health-related quality of life (HRQL) can evaluate the success and effect of transplant on patients’ lives through social, psychological, and physical health domains.² The HRQL records factors salient to patient health such as patient perspectives, as well as psychopathological and clinical status.^2-5 In the context of transplantation, measuring HRQL serves an alternative, yet equally important, outcome assessment versus patient complications or mortality.²

Lung transplant is a definitive treatment for end-stage lung disease. However, compared with other solid-organ transplants, lung transplant is associated with higher rates of rejection and lower rates of patient survival at 1 to 5 years after transplant. As such, lung transplant recipients tend to have lower HRQL,6 although the posttransplant HRQL is significantly improved at 6 months to 3 years after lung transplant.^7-14 The HRQL is a particularly important metric for lung transplant because many patients undergo lung transplant to improve HRQL, even though survival remains about 50% at 5 years.¹⁵ However, factors associated with patient HRQL have not been identified within this population. The goal of our study is to identify factors associated with HRQL among lung transplant recipients and candidates in our diverse patient population. By better understanding these factors, physicians can more directly identify risk factors in patients and develop interventions to target modifiable predictors and thereby maximize HRQL in transplant candidates and recipients.

Materials and Methods

Study design and setting

A single-center observational study was conducted at a large academic hospital in Chicago, Illinois. All protocols involving human subjects were approved by the Institutional Review Board (No. IRB20201124) before the study began, and the protocols conformed to the ethical guidelines of the 1975 Declaration of Helsinki. Written informed consent was obtained from the patients.

Study population

The study population of interest included all lung transplant candidates and recipients at our institution (≥18 years of age) from January 2021 to May 2022. All patients who received lung transplants during this time were eligible and provided consent for participation prior to completing the survey.

Patients were excluded from this study if they (1) had not received a transplant at our facility during the study period, (2) had received follow-up transplant care at a different facility, (3) were unable to read or speak English, and (4) had no residential telephone service or internet.

Survey tool for data collection

For this study, we used a modification of the validated RAND 36-Item Short Form Health Survey (SF-36; RAND Corporation) to assess HRQL in lung transplant candidates and recipients.¹⁶

The SF-36 questionnaire contains 36 discrete questions used to qualitatively assess patients’ perceived HRQL in the prior 4 weeks via 8 domains. Scores range from 0 to 100, and higher scores reflect higher HRQL. The 8 domains include the following: physical function, role limitations due to physical health problems, role limitations due to emotional problems, bodily pain, general health, vitality, social function, and mental health. By combining individual domains, the SF-36 survey yields 2 composite scores: the physical component summary (PCS) and the mental component summary (MCS). The questions included in the calculations for the 8 standard domains and summary categories are outlined in Table 1.

The final question included in the survey asked participants to rate their current status of health on a scale of 0 (death) to 100 (perfect). This value was recorded as their self-reported health score (SRHS).

Collected demographic and medical information

Electronic medical records were retrospectively reviewed to obtain demographic details (such as sex, race and ethnicity, and income) and medical information (such as pulmonary function tests and frailty assessment) for transplant candidates and recipients. For recipients, clinical outcomes were also reviewed. All information was stored in a REDCap database for both cohorts.¹⁷

In this study, patient frailty was determined with 2 well-regarded standardized assessments: the Fried frailty phenotype, which is an operationalized phenotype of frailty in older adults; and the modified 5-item frailty index (mFI-5), which is a comorbidity-based risk stratification tool that has shown promise for prediction of adverse surgical outcomes.^18,19 For the Fried frailty phenotype, patients are assessed on a scale of 0 to 5 (0 for no frailty, 1-2 for prefrailty, and 3-5 for frailty) based on the presence of the following signs and symptoms: unintentional weight loss >10 pounds or 5% of body mass in the prior year, weakness (measured by handgrip strength), exhaustion reported by the patient, slow gait speed (walking time over a distance of 15 feet), and low physical activity. These factors were assessed during candidate wait list evaluations. For the mFI-5 assessment, patients were scored on a scale of 0 to 5 at the time of the survey based on the presence of the following comorbidities at the time of surgery: hypertension (requiring medication), congestive heart failure within 30 days before surgery, respiratory problems (chronic obstructive pulmonary disease or current pneumonia or a predicted forced expiratory volume in 1 second of <70%), changes in everyday activity (Eastern Cooperative Oncology Group status >1), and a history of diabetes.

Statistical analyses

Descriptive analyses were performed to summarize the reviewed patient demographic and medical information and HRQL. Statistical software (R Foundation for Statistical Computing) was used to conduct the analyses on the acquired data.²⁰ Linear regression models were used to determine association of the collected demographic and clinical information with the overall HRQL, PCS, MCS, and SRHS. We determined significance levels for all analyses with the Fisher exact test and the Pearson chi-squared test, with significance estimated at α = 0.05.

Patient characteristics

Within the study period, 56 patients received a lung transplant at our institution. Among these patients, the mean age was 57.7 years (SD 13.1 years), 25% (14/56) were female, and 18% (10/56) identified as Black, 61% (34/56) as White, and 21% (12/56) as another race/ethnicity. Most of the lung transplants were bilateral (51/56), and the mean lung allocation score (LAS) was 57.8 (SD 23.7). During the same time period, there were 13930 lung transplant recipients within the United Network for Organ Sharing (UNOS). This cohort had a mean age of 57.7 years (SD 12.6 years), 40% (5549 of 13930) were female, and 10% (1359 of 13930) identified as Black, 78% (10 843 of 13930) as White, and 12% (1728 of 13 390) as another race/ethnicity.

Of the 48 candidates and recipients who were contacted, 28 (58.3%) responded to the survey; 11 were candidates on the wait list, and 17 were recipients within 2 years of lung transplant (Table 2). Overall, the median age was 61 years (IQR 55-66 years) for candidates and 64 years (IQR 57-70 years) for recipients, and 45% (5/11) of candidates and 6% (1/17) of recipients were female (P = .02) (Table 2). Within this cohort, 29% (8/28) identified as Black, 21% (6/28) as Hispanic or Latino, and 43% (12/28) as White. Of the recipients, 35% (6/17) were surveyed within 6 months, 29% (5/17) between 6 months and 1 year, and 35% (6/17) within 2 years of surgery.

Higher scores for the 36-Item Short-Form Health Survey among transplant recipients

Lung transplant recipients rated significantly higher levels in the SF-36 categories of physical function (60 vs 25; P = .03), vitality (60 vs 20; P = .009), general health (50 vs 30; P = .05), and social function (75 vs 50; P = .008) versus transplant candidates (Table 3). Recipients also had significantly higher ratings in the PCS (47.5 vs 33.8; P = .007), MCS (70.4 vs 58; P = .05), and SRHS (70 vs 50; P = .009) versus candidates. No significant differences were shown among the categories of bodily pain, mental health, and role limitations due to emotional problems.

Compared with transplant candidates, transplant recipients reported significant improvements in 4 of the 8 health domains: physical function (60 vs 25; P < .05), vitality (60 vs 20; P < .01), social function (75 vs 50; P < .01), and general health (50 vs 30; P = .05).

Factors associated with health-related quality of life

In lung transplant candidates, higher body mass index (BMI, body weight in kilograms divided height in meters squared) was significantly associated with lower PCS (-1.43; P = .016), and greater frailty with the mFI-5 scoring system was significantly associated with lower MCS (-9.11; P = .025). No significant associations were shown with the selected covariates for candidate SRHS. In recipients, however, higher BMI was significantly associated with lower PCS (-2.29; P = .046), and LAS was a significant predictor for SRHS (-0.33; P = .019). No significant associations were shown for recipient MCS (Table 4).

In this study, we demonstrated that transplant is associated with higher HRQL, and we identified BMI, mFI-5, and LAS to significantly affect HRQL outcomes in lung transplant candidates and recipients.

Our results support previous findings that lung transplants are associated with improved quality of life for the recipients.^7-14 In our study, recipients reported significantly higher physical function, mental health, social function, general health, and HRQL outcomes (PCS, MCS, and SRHS). In addition to worse lung function, which may affect physical HRQL domains, transplant candidates face unique stressors such as anxiety while (1) awaiting the procedure, (2) participating in several evaluations before candidacy, and (3) experiencing extended wait list durations, all of which decrease mental HRQL domains.²¹ One study by Napolitano and colleagues found that a telephone psychosocial intervention aimed to assist patients with stress management greatly affected patients’ perception of HRQL as they awaited transplant.²² Such interventions to address these obstacles encountered by lung transplant candidates may improve mental health (MCS) and overall perceived health (SRHS).

We found higher BMI to be significantly associated with lower PCS in both transplant candidates and recipients. Obesity has been associated with lower HRQL in the general population. Additionally, obesity has been associated with higher morbidity and mortality and with lower survival rates in transplant patients.²³ Our results agree with these prior findings. Across transplant candidates and recipients, increases in BMI may directly affect patient physical health (such as the ability to complete moderate or vigorous physical activity) and their overall PCS. Rodrigue and colleagues have reported similar results, and they discussed the need for greater vigilance in preoperative patient monitoring through dietary and weight loss programs.9 Evaluation of the efficacy of such programs could be an important contribution to transplant HRQL outcomes in relationship to BMI.

Several studies that evaluated the effect of transplant on HRQL have found frailty to be an important indicator in posttransplant outcomes.^24-26 For example, a study using the Short Physical Performance Battery frailty metric found that greater frailty was associated greater impairment post-transplant and lower HRQL in lung transplant recipients.²⁶ In our study, we used the Fried frailty phenotype, a physical-based frailty metric, and the mFI-5 index, a comorbidity-based frailty metric, as covariates in our HRQL models. Our results illustrated that higher mFI-5 scores were independently associated with lower patient MCS; however, we found no significant association with the Fried frailty phenotype. Transplant candidates may experience a variety of emotions and stressors associated with wait list status, transplant candidacy, or surgery outcomes. All of these factors may affect a candidate's mental health, and further complications may arise from the frailty-associated comorbidities such as those outlined in the mFI-5 index..²¹ Even in good perceived health, patients still may encounter challenges during adjustment or reintegration to their prior social roles, such as significant limitations in work activities or greater physical exertion to achieve fewer goals.

We determined higher LAS to be negatively associated with SRHS in transplant recipients. Valapour and colleagues compared low (<50), intermediate (50-75), and high (>75) LAS and observed that high LAS values were associated with lower survival and more hospital postoperative complications.6 Consistent with our study, patients who have been assigned higher priority based on LAS may face substantial health obstacles that affect perceived HRQL, both immediately and longitudinally.

Finally, our study included greater representation of racial and ethnic minority groups and medically underserved communities versus historical national demographic parameters and current demographic parameters within the UNOS cohort of lung transplant candidates and recipients.^6,27 Our patient population, from Chicago’s South Side, has experienced historically higher rates of chronic ailments and less access to medical care compared with other geographic populations in the United States.²⁸ Liu and colleagues found that lung transplants completed prior to 2000 in non-White patients (all who identified as “Black/African-American, Hispanic or Latino, Asian, American Indian or Alaskan Native, Native Hawaiian or Pacific Islander, or multiracial”) were associated with higher mortality and lower 5-year survival rates compared with White patients, independent of age, health, socioeconomic status, and demographic parameters.²⁹ Although we found no significant differences in clinical factors and HRQL outcomes across the cohort of White recipients and the cohort of all recipients who identified as a race/ethnicity other than White (data not shown), the demographic parameters of our study population may explain the lower postoperative HRQL scores versus other studies of patient groups with predominantly White race/ethnicity.

Our study has several limitations. Only a small cohort of patients at a single institution were enrolled in our study. Selection bias may be present, because patients were interviewed either face-to-face or via telephone and the responding patients were all surviving patients, benefitted from positive outcomes, and may have been more directly involved in their own self-care. Notwithstanding these limitations, our study includes both a diverse patient population and a comprehensive review of patient history to determine factors associated with HRQL. Moreover, the patient population within this study is enriched with the representation of more vulnerable, marginalized patients. Although our findings differ from the overall UNOS demographic parameters, the factors associated with HRQL may be generalizable and particularly applicable to transplant centers serving diverse populations. Nonetheless, these findings highlight the importance for development of interventions to target modifiable variables such as BMI and frailty.

Our study provided contemporary evidence of improvement in posttransplant HRQL and deter-mined that BMI, mFI-5, and LAS were all signi-ficantly associated with HRQL domains. From our findings, we emphasize the need for additional research to develop or identify interventions for the modifiable predictors to increase candidate and recipient HRQL.

Volume: 21 Issue: 7 July 2023

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