This cohort study evaluates the association of participation in mental health treatment, housing support, or employment support programs with stage at diagnosis, receipt of stage-appropriate treatment, and mortality among US veterans with a preexisting mental health disorder and a diagnosis of non–small cell lung cancer.
Key Points
Question
Is mental health treatment associated with improved outcomes for people with preexisting mental health disorders after they are diagnosed with cancer?
Findings
In this cohort study of 55 315 US veterans diagnosed with non–small cell lung cancer, 18 229 had a preexisting mental health disorder, among whom participation in mental health treatment programs was associated with a lower likelihood of being diagnosed with advanced cancer, a higher likelihood of receiving stage-appropriate treatment, and lower all-cause and lung cancer–specific mortality.
Meaning
The findings of this cohort study indicate that investment in mental health may be associated with improved cancer-related outcomes, but further research is needed to identify, evaluate, and implement effective interventions to improve outcomes for people with preexisting mental health disorders who are diagnosed with cancer.
Abstract
Importance
Preexisting mental health disorders (MHDs) are associated with increased mortality in people diagnosed with cancer, yet few data exist on the efficacy of interventions to mitigate this disparity.
Objective
To evaluate the association of participation in mental health treatment programs (MHTPs), housing support programs, or employment support programs with stage at cancer diagnosis, receipt of stage-appropriate treatment, and mortality among patients with a preexisting MHD.
Design, Setting, and Participants
This retrospective, population-based cohort study included 55 315 veterans in the Veterans Affairs Central Cancer Registry (VACCR) who had newly diagnosed non–small cell lung cancer (NSCLC) from September 30, 2000, to December 31, 2011. Data were analyzed from January 15, 2017, to March 17, 2020.
Exposures
Mental health disorders, including schizophrenia, bipolar disorder, depressive disorder, posttraumatic stress disorder, and substance use disorder.
Main Outcomes and Measures
Stage at cancer diagnosis, receipt of stage-appropriate cancer treatment, all-cause mortality, and lung cancer–specific mortality.
Results
Of 55 315 veterans with a new diagnosis of NSCLC included in the analysis (98.1% men; mean [SD] age, 68.1 [9.8] years), 18 229 had a preexisting MHD, among whom participation in MHTPs was associated with a lower likelihood of being diagnosed in a late stage (odds ratio [OR], 0.62; 95% CI, 0.58-0.66; P < .001), a higher likelihood of receiving stage-appropriate treatment (OR, 1.55; 95% CI, 1.26-1.89; P < .001), lower all-cause mortality (adjusted hazard ratio [AHR], 0.74; 95% CI, 0.72-0.77; P < .001), and lower lung cancer–specific mortality (AHR, 0.77; 95% CI, 0.74-0.80; P < .001). Likewise, participation in housing and employment support programs was associated with similar improvements in all outcomes described above.
Conclusions and Relevance
In veterans with preexisting MHDs diagnosed with NSCLC, participation in MHTPs and housing and employment support programs was associated with improved lung cancer–related outcomes. This study might be the first to demonstrate significant improvement in cancer mortality for patients with MHDs who participate in MHTPs, housing support programs, or employment support programs. This work supports substantial literature that investment in mental health and social needs can improve health outcomes and highlights the importance of further research to identify, evaluate, and implement interventions to improve outcomes for patients with MHDs who are diagnosed with cancer.
Introduction
Lung cancer remains the leading cause of cancer-related mortality in the United States, with most deaths attributed to non–small cell lung cancer (NSCLC).1 Studies evaluating the effects of preexisting mental health disorders (MHDs) on patients diagnosed with lung cancer universally find mental illness to be associated with increased mortality.2,3,4,5,6,7,8,9,10 Few data exist on the efficacy of interventions to mitigate disparities in cancer-related outcomes for patients with preexisting MHDs.
Mental health treatment programs (MHTPs) are integral to improving outcomes for patients with MHDs. The Veterans Health Administration (VHA) in the Department of Veterans Affairs (VA) is the largest health care system in the United States and provides an example of integrated behavioral health. The VHA aims to enhance well-being for all veterans by supporting primary care teams promoting activities connected with positive mental health. For those with MHDs and/or substance use disorder (SUD), MHTPs encompass a range of evidence-based interventions tailored to individual needs, with most including psychotherapy and/or medication. Social needs, such as housing and employment, are frequently connected with behavioral and physical health, and MHTPs can integrate with other VHA social and medical programs to collectively address complex health and social circumstances.11
Whether participation in MHTPs improves cancer-related outcomes among patients with preexisting MHDs has not, to our knowledge, been evaluated. The VHA is uniquely well suited to address this question for several reasons: (1) it consists of a large patient population with high rates of MHDs12; (2) it provides universal health care for eligible veterans; and (3) it compiles registries with patient-level data on cancer and mental health diagnoses and treatment. We conducted a large population-based cohort study of veterans to provide real-world data on the association of mental health treatment with cancer-related outcomes. Specifically, in veterans with preexisting MHDs and/or SUD, we investigated the association of participation in MHTPs, housing support programs, and employment support programs with stage at presentation, receipt of stage-appropriate treatment, all-cause mortality, and lung cancer–specific mortality. The potential for these findings to have pragmatic, real-world implications for management of patients with preexisting MHDs and a diagnosis of cancer is significant.
Methods
Study Population
We identified a cohort of patients diagnosed with NSCLC in the VHA from September 30, 2000, to December 31, 2011. Data for this study were obtained from the VA Central Cancer Registry (VACCR), as previously described,13 and the national VA electronic health record and fee-basis care (non-VA care paid for by the VA) housed in the Corporate Data Warehouse.14 Patients with NSCLC were identified from the VACCR using site codes for bronchus and lung and histology codes from the International Classification of Diseases for Oncology, Third Edition (eTable 1 in the Supplement).15,16 Patients were excluded if diagnosed by autopsy or if VACCR identification was inadequate to link to other VA databases, if they had missing or incomplete date of diagnosis, or if VACCR data had missing or discordant staging data as delineated by the contemporaneous American Joint Committee on Cancer Staging Manual. This process generated an initial cohort of 57 705 veterans diagnosed with NSCLC. Patients were excluded if they had a lung cancer diagnosis in the Corporate Data Warehouse more than 1 year before their first date of diagnosis in the VACCR, did not have at least 1 visit in the VA health care system during the year before diagnosis, and if a date of death occurred before lung cancer diagnosis, for a final analytic cohort of 55 315 veterans with NSCLC (eFigure 1 in the Supplement). This study was approved by the San Francisco VA and UCSF (University of California, San Francisco) Committee on Human Research. A waiver of informed consent was approved by the institutional review board because the study was conducted using previously collected electronic health records and the research involved no more than minimal risk to patients. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Variables
We identified the following MHDs using diagnosis codes from the International Classification of Disease, Ninth Edition (ICD-9) listed twice in the outpatient setting or once in the inpatient setting 1 year before NSCLC diagnosis: schizophrenia, bipolar disorder, depressive disorder, anxiety disorder, posttraumatic stress disorder (PTSD), and SUD.17 The other MHD group includes patients with ICD-9 diagnosis codes 290 to 310 not included in the other specified MHDs except for dementia and tobacco use disorder (eTable 1 in the Supplement). The any MHD group includes patients meeting criteria for the 6 specified MHDs or other MHD. The no MHD group was defined as those patients who did not meet the definition for the any MHD group as defined above. We then evaluated participation in evidence-based programs designed to address mental health, substance use, homelessness, and unemployment as risk factors for outcomes. Specific programs evaluated include mental health intensive case management for schizophrenia and bipolar disorder, psychotherapy for depressive and anxiety disorders, PTSD therapy, and substance use treatment programs. Program participation was ascertained from Current Procedural Terminology codes and VA stop codes, an internal coding system used to capture workload data.18,19,20
Outcome Variables
We compared the hazard of mortality between (1) patients with individual MHDs vs those with no MHD and (2) patients with individual MHDs who did vs did not participate in evidence-based MHTPs specific to that MHD. Patients with multiple MHDs were included in the analysis for each individual MHD. For all-cause mortality, patients were followed from the date of diagnosis until death or administrative censoring at 5 years; for lung cancer–specific mortality, patients were also censored for death due to causes other than NSCLC. Dates of death were determined from the VA Vital Status File.21 Cause-of-death data were obtained from the Center for Excellence Suicide Data Repository–National Death Index. Stage at diagnosis was determined using the contemporaneous American Joint Committee on Cancer clinical staging classification. Receipt of stage-appropriate treatment was determined based on contemporaneous National Comprehensive Cancer Network guidelines for NSCLC: surgery or stereotactic body radiotherapy for stage I (localized) disease; multimodality treatment with at least 2 therapies (surgery or radiotherapy with chemotherapy or all 3 modalities) for stage II/III (locoregional) disease; and chemotherapy or targeted therapy for stage IV (metastatic) disease. Receipt of treatment was ascertained via VACCR codes and Current Procedural Terminology codes from VACCR and VA databases, respectively, including fee basis data.
Covariates
Additional variables thought to influence outcomes, including age at lung cancer diagnosis, year of diagnosis, sex, race, marital status, smoking history, and substance use, were determined from VA data. Comorbid illness (other than lung cancer) was quantified using the enhanced Charlson comorbidity index.22
Statistical Analysis
Data were analyzed from January 15, 2017, to March 17, 2020. Patient characteristics were compared using the χ2 test (categorical variables) and 2-tailed t test (continuous variables). Unadjusted and adjusted hazards of all-cause mortality and lung cancer–specific mortality comparing patients with and without MHDs were estimated using Cox proportional hazards regression models. We evaluated adjusted odds of diagnosis with late-stage (III/IV) vs early-stage (I/II) NSCLC between patients with MHDs who did vs did not participate in MHTPs. We then evaluated adjusted odds of receiving stage-appropriate treatment between patients with MHDs who did vs did not participate in MHTPs. Finally, we compared unadjusted and adjusted hazards of all-cause mortality and lung cancer–specific mortality between patients with MHDs who did vs did not participate in MHTPs. Multivariate models were adjusted for age, sex, race, marital status, Charlson comorbidity score, smoking status (never, former, or current), substance use (except for patients with SUD), and year of diagnosis unless otherwise noted in individual tables. Statistical significance threshold was set at 2-sided P < .05. All analyses were conducted using SAS Enterprise Guide software, version 7.1 (SAS Institute Inc).
Results
Patient Characteristics
Baseline characteristics of the 55 315 veterans with NSCLC in this cohort (1045 women [1.9%] and 54 261 men [98.1%] among those with available data; mean [SD] age, 68.1 [9.8] years) are provided in Table 1. Compared with patients with no MHD, those with MHDs were significantly younger (mean [SD] age, 65.1 [9.6] vs 69.6 [9.5] years), had more comorbidities (>3 comorbidities, 6141 [33.7%] vs 12 009 [32.4%]), and were more likely to be current smokers (10 982 [64.2%] vs 18 058 [52.3%]) and unmarried (10 977 [60.2%] vs 18 963 [51.1%]) (P < .001 for all). Most patients with MHDs (10 364 [56.9%]) participated in at least 1 MHTP (eTable 2 in the Supplement). Among patients with MHDs, those who participated in MHTPs were younger (mean [SD] age, 63.5 [9.3] vs 67.2 [9.6] years), had fewer comorbidities (>3 comorbidities, 3266 [31.5%] vs 2875 [36.6%]), were more likely to be current smokers (6439 [66.2%] vs 4543 [61.5%]), and were less likely to be married (3876 [37.4%] vs 3212 [40.8%]) (P < .001 for all).
Table 1. Characteristics of Veterans With Non–Small Cell Lung Cancer (NSCLC).
| Characteristic | Diagnostic or treatment groupa | |||
|---|---|---|---|---|
| No MHD (n = 37 086) | Any MHD (n = 18 229) | Any MHD in MHTP (n = 10 364) | Any MHD not in MHTP (n = 7865) | |
| Age at diagnosis, mean (SD), y | 69.6 (9.5) | 65.1 (9.6) | 63.5 (9.3) | 67.2 (9.6) |
| Sex | ||||
| Female | 577 (1.6) | 468 (2.6) | 322 (3.1) | 146 (1.9) |
| Male | 36 505 (98.4) | 17 756 (97.4) | 10 039 (96.9) | 7717 (98.1) |
| Charlson comorbidity score | ||||
| 0 | 6388 (17.2) | 2693 (14.8) | 1629 (15.7) | 1064 (13.5) |
| 1-3 | 18 689 (50.4) | 9395 (51.5) | 5469 (52.8) | 3926 (49.9) |
| >3 | 12 009 (32.4) | 6141 (33.7) | 3266 (31.5) | 2875 (36.6) |
| Race | ||||
| White | 29 430 (80.4) | 14 133 (78.3) | 7791 (75.9) | 6342 (81.5) |
| Black | 6142 (16.8) | 3397 (18.8) | 2122 (20.7) | 1275 (16.4) |
| Other | 1010 (2.8) | 516 (2.9) | 347 (3.4) | 169 (2.2) |
| Smoking status | ||||
| Never | 1251 (3.6) | 460 (2.7) | 263 (2.7) | 197 (2.7) |
| Former | 15 218 (44.1) | 5666 (33.1) | 3018 (31.0) | 2648 (35.8) |
| Current | 18 058 (52.3) | 10 982 (64.2) | 6439 (66.2) | 4543 (61.5) |
| Marital status | ||||
| Single | 2713 (7.3) | 2009 (11.0) | 1302 (12.6) | 707 (9.0) |
| Married | 17 717 (47.8) | 7088 (38.9) | 3876 (37.4) | 3212 (40.8) |
| Previously married | 16 250 (43.8) | 8968 (49.2) | 5108 (49.3) | 3860 (49.1) |
| Unknown | 406 (1.1) | 164 (0.9) | 78 (0.8) | 86 (1.1) |
Abbreviations: MHD, mental health disorder; MHTP, mental health treatment program.
Unless otherwise indicated, data are expressed as number (percentage) of participants. Numbers may not sum to column totals owing to missing data. Percentages have been rounded and may not total 100. P < .001 for all patient characteristics between veterans with no vs any MHD and veterans with any MHD participating vs not participating in MHTPs.
Association of MHD With Mortality
A total of 48 310 patients (87.3%) died during the study, with a median follow-up of 8.9 (range, 1-60) months; most of these (39 655 [82.1%]) died of lung cancer. Adjusted hazard ratios (AHRs) of all-cause mortality and lung cancer–specific mortality associated with MHDs are summarized in Table 2. Cox proportional hazards regression analysis adjusted for baseline patient differences, stage at presentation, and rates of stage-appropriate treatment found that patients with any MHD had increased all-cause mortality (AHR, 1.03; 95% CI, 1.01-1.06; P = .008) and lung cancer–specific mortality (AHR, 1.03; 95% CI, 1.01-1.06; P = .02). Schizophrenia and other MHD were the only individual MHDs associated with an increased hazard of all-cause mortality (AHRs, 1.09 [95% CI, 1.03-1.16; P = .047] and 1.09 [95% CI, 1.04-1.13; P < .001], respectively) and lung cancer–specific mortality (AHRs, 1.10 [95% CI, 1.02-1.18; P = .01] and 1.07 [95% CI, 1.02-1.13; P = .006], respectively).
Table 2. Hazard of Mortality by Mental Health Disorder.
| Mental health disorder | No. of patients | Outcome, AHR (95% CI)a | |
|---|---|---|---|
| All-cause mortality | Lung cancer–specific mortality | ||
| Any | 18 229 | 1.03 (1.01-1.06)b | 1.03 (1.01-1.06)b |
| Schizophrenia | 1426 | 1.09 (1.03-1.16)c | 1.10 (1.02-1.18)b |
| Bipolar disorder | 806 | 0.99 (0.91-1.07) | 0.96 (0.87-1.07) |
| Depressive disorder | 7953 | 0.98 (0.95-1.01) | 1.00 (0.97-1.03) |
| Anxiety disorder | 6383 | 0.97 (0.95-1.00) | 1.00 (0.96-1.04) |
| PTSD | 3645 | 0.94 (0.90-0.97)c | 0.96 (0.92-1.01) |
| SUD | 5596 | 1.01 (0.97-1.04) | 1.00 (0.96-1.04) |
| Other | 2465 | 1.09 (1.04-1.13)d | 1.07 (1.02-1.13)b |
Abbreviations: AHR, adjusted hazard ratio; PTSD, posttraumatic stress disorder; SUD, substance use disorder.
Reference group for all AHRs consists of patients with no mental health disorder.
P < .05.
P < .005.
P < .001.
Association of MHTPs With Stage at Presentation
Patients with MHDs who participated in MHTPs were more likely to be diagnosed with early-stage NSCLC (Table 3). The adjusted odds ratio (AOR) for patients with any MHD who participated in an MHTP of being diagnosed with late-stage disease was 0.62 (95% CI, 0.58-0.66; P < .001) compared with patients who did not participate in an MHTP. Similar results were observed for patients with bipolar disorder (AOR, 0.64; 95% CI, 0.41-0.99), depressive disorder (AOR, 0.64; 95% CI, 0.58-0.72), anxiety disorder (AOR, 0.56; 95% CI, 0.49-0.63), PTSD (AOR, 0.82; 95% CI, 0.70-0.96), and SUD (AOR, 0.66; 95% CI, 0.58-0.75) (P < .05 for all). The odds of being diagnosed with late-stage disease was also significantly lower for patients who participated in housing support programs (AOR, 0.64; 95% CI, 0.56-0.73; P < .001) and employment support programs (AOR, 0.64; 95% CI, 0.52-0.78; P < .001).
Table 3. Odds of Diagnosis With Late- vs Early-Stage Disease Based on Program Participation.
| Mental health disordera | Late- vs early-stage disease, AOR (95% CI)b |
|---|---|
| Any | |
| Mental health treatment program | 0.62 (0.58-0.66)c |
| Housing support | 0.64 (0.56-0.73)c |
| Employment support | 0.64 (0.52-0.78)c |
| Schizophrenia | 0.80 (0.57-1.11) |
| Bipolar disorder | 0.64 (0.41-0.99)d |
| Depressive disorder | 0.64 (0.58-0.72)c |
| Anxiety disorder | 0.56 (0.49-0.63)c |
| PTSD | 0.82 (0.70-0.96)d |
| SUDd | 0.66 (0.58-0.75)c |
Abbreviations: AOR, adjusted odds ratio; MHTP, mental health treatment program; PTSD, posttraumatic stress disorder; SUD, substance use disorder.
Program was MHTP unless otherwise noted; program for SUD was substance use treatment.
Reference group for each mental health disorder (MHD) consists of patients with that MHD who did not participate in the program. Early stage indicates I to II; late, III to IV. Odds are based on program participation.
P < .001.
P < .05.
Association of MHTPs With Receipt of Stage-Appropriate Treatment
Participation in MHTPs significantly increased the likelihood that patients with preexisting MHDs received stage-appropriate treatment (Table 4). Among patients with any MHD, participation in a MHTP was associated with a significant increase in the odds of receiving any stage-appropriate treatment (AOR, 1.55; 95% CI, 1.26-1.89; P < .001) and stage-appropriate treatment for stage I (AOR, 1.34; 95% CI, 1.17-1.54; P < .001), stages II to III (AOR, 1.17; 95% CI, 1.04-1.32; P = .008), and stage IV (AOR, 1.12; 95% CI, 1.01-1.23; P = .04) disease (eTable 3 in the Supplement). Likewise, among patients with any MHD, those who participated in housing support programs (AOR, 1.15; 95% CI, 1.01-1.31; P = .03) or employment support programs (AOR, 1.30; 95% CI, 1.22-1.39; P < .001) were more likely to receive stage-appropriate treatment for all stages of NSCLC. Participation in MHTPs was associated with a significant increase in the odds of receiving stage-appropriate treatment for patients with depressive disorder (AOR, 1.36; 95% CI, 1.23-1.51), anxiety disorder (AOR, 1.42; 95% CI, 1.26-1.60), PTSD (AOR, 1.41; 95% CI, 1.22-1.64), and SUD (AOR, 1.43; 95% CI, 1.26-1.62) (P < .001 for all). Further, patients with depressive disorder (AOR, 1.45; 95% CI, 1.17-1.80), anxiety disorder (AOR, 1.43; 95% CI, 1.10-1.85), and SUD (AOR, 1.68; 95% CI, 1.29-2.20) who participated in MHTPs were significantly more likely to receive stage-appropriate treatment for stage I NSCLC than those who did not participate (P < .05 for all).
Table 4. Odds of Receiving Stage-Appropriate Treatment Based on Program Participation.
| Mental health disordera | Receipt of stage-appropriate treatment, AOR (95% CI)b |
|---|---|
| Any | |
| Mental health treatment program | 1.55 (1.26-1.89)c |
| Housing support | 1.15 (1.01-1.31)d |
| Employment support | 1.30 (1.22-1.39)c |
| Schizophrenia | 0.92 (0.67-1.26) |
| Bipolar disorder | 0.77 (0.51-1.16) |
| Depressive disorder | 1.36 (1.23-1.51)c |
| Anxiety disorder | 1.42 (1.26-1.60)c |
| PTSD | 1.41 (1.22-1.64)c |
| SUDd | 1.43 (1.26-1.62)c |
Abbreviations: AOR, adjusted odds ratio; MHTP, mental health treatment program; PTSD, posttraumatic stress disorder; SUD, substance use disorder.
Program was MHTP unless otherwise noted; program for SUD was substance use treatment.
Reference group for each mental health disorder consists of patients with that disorder who did not participate in the program. Odds are based on program participation.
P < .001.
P < .05.
Association of MHTPs With Mortality
After adjusting for baseline differences, stage at diagnosis, and rates of stage-appropriate treatment, participation in a MHTP was associated with a significant decrease in all-cause mortality and lung cancer–specific mortality across every MHD evaluated, including schizophrenia (AHRs, 0.79 [95% CI, 0.68-0.92] and 0.74 [95% CI, 0.62-0.88], respectively), bipolar disorder (AHRs, 0.79 [95% CI, 0.64-0.98] and 0.76 [95% CI, 0.59-0.98], respectively), depressive disorder (AHRs, 0.70 [95% CI, 0.67-0.74] and 0.73 [95% CI, 0.69-0.78], respectively), anxiety disorder (AHRs, 0.72 [95% CI, 0.67-0.76] and 0.75 [95% CI, 0.70-0.80], respectively), PTSD (AHRs, 0.81 [95% CI, 0.74-0.87] and 0.80 [95% CI, 0.73-0.87], respectively), and SUD (AHRs, 0.74 [95% CI, 0.69-0.79] and 0.74 [95% CI, 0.69-0.80], respectively) (P < .05 for all) (Table 5). The adjusted hazard of all-cause mortality among patients with any MHD participating in the following programs was 0.74 (95% CI, 0.72-0.77) for any MHTP, 0.72 (95% CI, 0.67-0.77) for housing support programs, and 0.73 (95% CI, 0.65-0.82) for employment support programs (P < .001 for all). The AHR of lung cancer–specific mortality among patients with any MHD participating in the following programs was 0.77 (95% CI, 0.74-0.80) for any MHTP, 0.70 (95% CI, 0.65-0.76) for housing support programs, and 0.80 (95% CI, 0.70-0.90) for employment support programs (P < .001 for all). These results were consistent across patient subgroups (eTable 4 in the Supplement). Kaplan-Meier curves for all-cause mortality and lung cancer–specific mortality are shown in eFigures 2 and 3 in the Supplement.
Table 5. Hazard of Mortality Based on Program Participation.
| Mental health disordera | AHR (95% CI)b | |
|---|---|---|
| All-cause mortality | Lung cancer–specific mortality | |
| Any | ||
| Mental health treatment program | 0.74 (0.72-0.77)c | 0.77 (0.74-0.80)c |
| Housing support | 0.72 (0.67-0.77)c | 0.70 (0.65-0.76)c |
| Employment support | 0.73 (0.65-0.82)c | 0.80 (0.70-0.90)c |
| Schizophrenia | 0.79 (0.68-0.92)d | 0.74 (0.62-0.88)d |
| Bipolar disorder | 0.79 (0.64-0.98)e | 0.76 (0.59-0.98)e |
| Depressive disorder | 0.70 (0.67-0.74)c | 0.73 (0.69-0.78)c |
| Anxiety disorder | 0.72 (0.67-0.76)c | 0.75 (0.70-0.80)c |
| PTSD | 0.81 (0.74-0.87)c | 0.80 (0.73-0.87)c |
| SUDe | 0.74 (0.69-0.79)c | 0.74 (0.69-0.80)c |
Abbreviations: AHR, adjusted hazard ratio; MHTP, mental health treatment program; PTSD, posttraumatic stress disorder; SUD, substance use disorder.
Program was MHTP unless otherwise noted; program for SUD was substance use treatment.
Adjusted model includes baseline patient characteristics (see Methods section), stage at diagnosis, and receipt of stage-appropriate treatment. Reference group for each mental health disorder (MHD) consists of patients with that MHD who did not participate in the program.
P < .001.
P < .005.
P < .05.
Discussion
Our results concur with those of several prior studies that preexisting MHDs are associated with increased mortality among patients diagnosed with NSCLC.2,3,4,5,6,7,8,9,10 Whether treatment of MHDs affects cancer-related outcomes remains an important unanswered question.23 Our study sought to evaluate the association of mental health treatment and addressing social determinants of health with stage at cancer diagnosis, receipt of stage-appropriate treatment, and cancer mortality. Overall, we demonstrated in this large population-based study of veterans with preexisting MHDs diagnosed with NSCLC that participation in MHTPs, housing support programs, and employment support programs was associated with improved cancer-related outcomes, including a lower likelihood of being diagnosed with late-stage disease, a higher likelihood of receiving stage-appropriate treatment, and lower all-cause mortality and lung cancer–specific mortality compared with nonparticipants.
It is important to consider why these programs may be so effective. The potential explanations are varied and multifactorial. In a randomized study of patients with depression,24 the combination of pharmacotherapy and psychotherapy resulted in significant improvements in mental health, general health, physical functioning, and social functioning. In the context of our study, patients who engaged in MHTPs with resulting improvement of their mental illness could potentially engage more with their non–mental health medical treatment. Consequently, they may more likely be diagnosed with early-stage disease and receive stage-appropriate treatment than nonparticipants. Further, reductions in mental illness severity may manifest in greater self-efficacy for managing chronic conditions and improvement in other positive health behaviors such as diet, physical activity, and stress management. Another potential explanation is the interaction between mental health and the immune system. Given that depression and stress are shown to suppress cytokine production, cytotoxic T-cell activity, and natural killer cell activity, treating MHDs may modulate the immune response, thus improving cancer outcomes.25
Social needs, in addition to MHDs and SUD, are associated with worse health outcomes. Among patients with MHDs and/or SUD, we observed that participation in employment and housing support programs was associated with earlier stage at diagnosis, increased rates of stage-appropriate treatment, and decreased all-cause mortality and lung cancer–specific mortality. Although this finding is novel in patients diagnosed with cancer, similar outcomes have been observed in the population with HIV/AIDS. Among people living with HIV/AIDS, SUD is associated with lower rates of viral load testing,26 lower rates of antiretroviral therapy,27 and higher viral load,28 whereas treatment for SUD reduces addiction severity and improves adherence to antiretroviral therapy.29 Evaluation of housing support programs also supports the potential effect of addressing homelessness on health outcomes. In a prospective study of homeless individuals enrolled in a program that provided housing,30 harm reduction, and peer support, 98% of participants remained housed after 12 months, and individuals who were housed reported significant increases in their quality of life as well as access to and use of planned health care services. Our work further supports that investment in behavioral health and social needs can improve health outcomes in concert with medical care.
Finally, the VHA is a government-funded health system with legally chartered duties to comprehensively serve a population. The VHA has alignment of financial and quality incentives that lend to integration of behavioral health and social needs into the health system, with primary care as the center of care delivery. With an integrated health system, oncologists, primary care physicians, nurses, behavioral health specialists, and community health workers can communicate and coordinate care for complex patients, empowering cross-disciplinary collaboration. At a population level, the VHA has invested in behavioral health and social need programs that potentially have a greater effect on health outcomes than investments in health care delivery.31 Finally, the VHA system centers around interdisciplinary primary care. Primary care at the center of a patient’s health system leads to better management of chronic disease, including MHDs and/or SUD, and potentially earlier cancer screening and diagnosis and adherence to cancer treatment. Each of these characteristics likely contributes to the association of VHA MHTPs with cancer-related outcomes and mortality.
Colocated palliative care demonstrates how an integrated approach can improve outcomes for patients with cancer. Early palliative care significantly improves quality of life and prolongs survival for patients with metastatic NSCLC.32 When palliative care is colocated with the patient’s oncology clinic, the patient is almost 20 times more likely to see a palliative care specialist and benefit from these services.33 Similarly, reductions in mortality reported in this study are likely in part owing to primary care mental health integration in the VHA.
Limitations
Our study has several limitations. We were unable to evaluate MHD severity, and the use of ICD-9 coding to define MHDs may lead to misclassification. Further, our study did not identify those diagnosed with MHDs after the cancer diagnosis or who remain undiagnosed by clinicians. Treatment data were collected from VA databases within 6 months of NSCLC diagnosis and may not fully capture treatment administered outside the VHA or outside this time window. Inherent to studies performed within the VHA, our cohort consists almost entirely of men; the validity of generalizing these results to women is not clear. An inherent limitation of large retrospective studies is the reliance on billing codes to capture data of interest, which could underestimate treatment rates and does not capture the extent to which patients participated in MHTPs. The finding that patients who participated in MHTPs were younger and had fewer comorbidities may reflect selection bias. Further, healthy user bias, whereby patients participating in MHTPs are more likely to take better care of their health generally, is a potential confounding variable. Although multivariate models were used to adjust outcomes of interest for intergroup differences, residual confounding may be present. Preclinical and population-based studies have attributed both procancer and anticancer properties to various psychotropic medications. We did not explore this relationship in our cohort and so cannot exclude the possibility that there may be unmeasured effects of psychotropic medications on the outcomes reported in this study. Finally, patients in this cohort were treated in the VHA, which provides universal health care for eligible veterans, decreasing barriers to obtaining mental health treatment and medical care. Whether these results apply to patients treated outside of the VHA will need to be evaluated.
Conclusions
In summary, we found that among veterans diagnosed with NSCLC, preexisting MHDs were associated with increased mortality. However, patients with MHDs who participated in MHTPs, housing support programs, and employment support programs had improved lung cancer–related outcomes with earlier stage at diagnosis, higher rates of stage-appropriate treatment, and lower all-cause and lung cancer–specific mortality compared with nonparticipants. Our work supports substantial literature that investment in behavioral health and social needs can improve health outcomes and enhance delivery of medical care. Specifically, increasing participation in MHTPs and providing housing and employment support programs might be very helpful in improving lung cancer–related outcomes in patients with MHDs. This work supports the importance of additional research to identify, evaluate, and implement effective interventions to improve outcomes for people with MHDs who are diagnosed with cancer.
eTable 1. ICD-O-3 and ICD-9 Codes Used to Define Clinical Variables
eTable 2. Number of Patients With MHDs Who Participated in MHTPs, SUTPs, Housing Support Programs, and Employment Support Programs
eTable 3. Odds of Receipt of Stage-Appropriate Treatment by Stage Based on Program Participation
eTable 4. Subgroup Analysis of Mortality for Patients With Any MHD Based on MHTP Participation
eFigure 1. CONSORT Diagram
eFigure 2. Kaplan-Meier Curves for All-Cause Mortality Based on MHTP Participation
eFigure 3. Kaplan-Meier Curves for Lung Cancer–Specific Mortality Based on MHTP Participation
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. ICD-O-3 and ICD-9 Codes Used to Define Clinical Variables
eTable 2. Number of Patients With MHDs Who Participated in MHTPs, SUTPs, Housing Support Programs, and Employment Support Programs
eTable 3. Odds of Receipt of Stage-Appropriate Treatment by Stage Based on Program Participation
eTable 4. Subgroup Analysis of Mortality for Patients With Any MHD Based on MHTP Participation
eFigure 1. CONSORT Diagram
eFigure 2. Kaplan-Meier Curves for All-Cause Mortality Based on MHTP Participation
eFigure 3. Kaplan-Meier Curves for Lung Cancer–Specific Mortality Based on MHTP Participation