
==== Front
Perm J
tpj
tpj
The Permanente Journal
1552-5767
1552-5775
The Permanente Press

38980792
10.7812/TPP/24.028
TPJ-24-028
Original Research
Representativeness of Patients With Lung Cancer in an Integrated Health Care Delivery System
Yang Mike Z MD 1
http://orcid.org/0000-0002-4667-9632
Liu Raymond MD 2 3
Von Behren Julie MPH 4
Lin Katherine MPH 4
Adams Alyce S PhD 5
Kushi Lawrence H ScD 3
Quesenberry Charles P Jr PhD 3
Velotta Jeffrey B MD, FACS 6
Wong Melisa L MD, MAS, AGSF 3 7
Young-Wolff Kelly C PhD 3 8
Gomez Scarlett L PhD, MPH 4
Shariff-Marco Salma PhD, MPH 4
http://orcid.org/0000-0002-0900-5735
Sakoda Lori C PhD, MPH 3 8
1 Internal Medicine Residency, Kaiser Permanente Northern California, San Francisco, CA, USA
2 Department of Medical Oncology, Kaiser Permanente Northern California, San Francisco, CA, USA
3 Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
4 Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
5 Department of Health Policy, Stanford University School of Medicine, Stanford, CA, USA
6 Department of Thoracic Surgery, Kaiser Permanente Northern California, Oakland, CA, USA
7 Division of Geriatrics, University of California, San Francisco, San Francisco, CA, USA
8 Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA
Lori C Sakoda, PhD, MPH lori.sakoda@kp.org
2024
12 6 2024
28 3 1322
© 2024 The Authors.
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Published by The Permanente Federation LLC under the terms of the CC BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.

Abstract

Introduction

Observational research is important for understanding the real-world benefits of advancements in lung cancer care. Integrated health care systems, such as Kaiser Permanente Northern California, have extensive electronic health records suitable for such research, but the generalizability of their populations is often questioned.

Methods

Leveraging data from the California Cancer Registry, the authors compared distributions of demographic and clinical characteristics, in addition to neighborhood and environmental conditions, between patients diagnosed with lung cancer from 2015 through 2019 at Kaiser Permanente Northern California, National Cancer Institute-designated cancer centers (NCICCs), and all other non-NCICC hospitals within the same catchment area.

Results

Of 20,178 included patients, 30% were from Kaiser Permanente Northern California, 8% from NCICCs, and 62% from other non-NCICC hospitals. Compared to NCICC patients, Kaiser Permanente Northern California patients were more similar to other non-NCICC patients on most characteristics. Compared to other non-NCICC patients, Kaiser Permanente Northern California patients were slightly older, more likely to be female, and less likely to be Hispanic or Asian/Pacific Islander and to reside in lower socioeconomic status (SES) neighborhoods. In contrast, NCICC patients were younger, less likely to be female or from non-Asian/Pacific Islander minoritized racial groups, and more likely to present with early-stage disease and adenocarcinoma and to reside in neighborhoods with higher SES and lower air pollution than Kaiser Permanente Northern California or other non-NCICC patients.

Discussion

Patients from Kaiser Permanente Northern California, compared to NCICCs, are more broadly representative of the underlying patient population with lung cancer.

Conclusion

Research using electronic health record data from integrated health care systems can contribute generalizable real-world evidence to benchmark and improve lung cancer care.

Keywords:

Lung cancer
integrated health care systems
observational research
the National Cancer Institute at the National Institutes of Health R01 CA263322 to L.C.S.
==== Body
pmcIntroduction

Lung cancer remains the leading cause of cancer death and the second most diagnosed cancer in the United States.1 In the past decade, promising advances in risk reduction through sustained campaigns against tobacco use, screening with low-dose computed tomography, and treatments against molecular targets have reduced the lung cancer burden.2,3 These advances have largely come by way of randomized clinical trials (RCTs), which remain the gold standard for shaping evidence-based medicine.4 Unfortunately, patients with cancer in the community often see reduced benefit compared to patients in clinical trials receiving the same intervention,5–8 an observation that reflects limitations to the external validity of RCTs and the need for observational research to evaluate the real-world effectiveness of RCT findings.4–9 Especially when conducted in highly diverse and representative populations, observational studies can improve lung cancer care by offering valuable insight into real-world outcomes.

With electronic health records (EHRs) containing vast amounts of detailed clinical information, large integrated health systems, such as those within the National Cancer Institute (NCI)-funded Cancer Research Network, are well positioned to conduct cancer research using EHR data that is more clinically relevant than those from population-based cancer registries.10–13 Because integrated health care systems often cover only segments of a population, there are often concerns regarding the generalizability of their patient data. However, based on California Cancer Registry data from 1996 to 2009, the authors previously demonstrated that patients with breast cancer diagnosed at a large integrated health care system in Northern California were more clinically, demographically, and socioeconomically representative of the general population than patients with breast cancer diagnosed at NCI-designated cancer centers (NCICCs) within the same geographic region.10 To the authors’ knowledge, this comparison has not been evaluated specifically in lung cancer despite its high burden in the United States.

In the present study, the authors evaluated the representativeness of patients with lung cancer from Kaiser Permanente Northern California, the largest integrated health care system in Northern California. The authors compared their demographic, clinical, and neighborhood characteristics with those of patients with lung cancer from NCICCs and all other hospitals within the same catchment area.

Methods

Study population

The study population included all patients with a first primary invasive lung cancer based on the International Classification of Diseases for Oncology, 3rd Edition, codes C34.0–C34.9. Patients were diagnosed from January 1, 2015, to December 31, 2019, as reported to the California Cancer Registry (part of the NCI’s Surveillance, Epidemiology, and End Results program), and whose county of residence at time of diagnosis was within the Kaiser Permanente Northern California catchment area. The catchment counties—defined as any county in Northern California in which at least 10% of the total lung cancer cases were diagnosed at a Kaiser Permanente Northern California facility—included Alameda, Amador, Contra Costa, El Dorado, Fresno, Madera, Marin, Napa, Placer, Sacramento, San Francisco, San Joaquin, San Mateo, Santa Clara, Solano, Sonoma, Stanislaus, Yolo, and Yuba. Cases were assigned to 2010 US Census tracts based on residential address at time of diagnosis. Informed consent was not required for analysis of deidentified cancer registry data. The authors’ protocol was approved under the Greater Bay Area Cancer Registry Institutional Review Boad protocol at the University of California, San Francisco.

Patients were designated as belonging to Kaiser Permanente Northern California hospitals, NCICCs, or all other hospitals (non-NCICCs), based on the earliest recorded encounter for their cancer. The NCICCs in the relevant catchment area were Stanford University; University of California, Davis; and University of California, San Francisco.

Patient characteristics

Individual patient characteristics, including age, sex, race and ethnicity, insurance or payer status, comorbidity burden, cancer stage, and tumor histology at time of diagnosis, were directly extracted from the California Cancer Registry database. Health insurance status was based on both primary and secondary payer sources. Comorbidity burden was measured using the Charlson Comorbidity Index (based on linkage to statewide hospitalizations data), which has been validated for predicting outcomes in many lung cancer patient groups.14–16

Neighborhood-level attributes

Neighborhood-level attributes were determined for patients based on their 2010 US Census tract of residence at the time of cancer diagnosis, including neighborhood socioeconomic status (nSES), Asian enclave index, Hispanic enclave index, racial and ethnic composition, population density, and rurality.17 nSES is a widely used measure derived from a principal component analysis of seven factors from the American Community Survey (2007–2011).18–20 These factors include median household income, Liu education index,21,22 percentage < 200% of poverty line, proportion with blue collar occupation, proportion unemployed, median rent, and median house value. Asian and Hispanic ethnic enclave indices were based on principal components analysis and included variables on percentage racial/ethnic group, percentage foreign-born, percentage recent immigrants, linguistic isolation, and English proficiency.17 Racial and ethnic composition measures were based on the total population of Hispanic/Latino, Asian American, Black, and White residents. Population density was calculated by dividing the total population of the census tract by its land area in square miles. Urban and rural classification was determined from the proportion of the census tract population that resided in a census block defined as urban, based on total population thresholds, population density, land use, and distance to other urban development.23

Environmental pollution attributes

Environmental indicators were obtained from the California Office of Environmental Health Hazard Assessment’s CalEnviroScreen, version 4.0 (CES).24 This publicly available resource uses various environmental, health, and socioeconomic measures to identify California communities affected by multiple sources of pollution. The authors selected two CES pollution indicators, overall pollution burden score and outdoor air fine particulate matter (PM2.5; referring to concentrations of particulate matter ≤ 2.5microns in diameter per cubic meter of air based on annual mean concentrations) and assigned them at the census tract level. The overall pollution score weighs potential environmental exposures from 12 sources: ozone, PM2.5, diesel, drinking water contamination, agricultural pesticide use, toxic releases, traffic density, cleanup sites, hazardous waste, groundwater threats, impaired bodies of water, and solid waste sites. The outdoor air pollution data comes from the California Air Resources Board’s monitoring network. Detailed descriptions of the methods used for each of these pollution indicators are available online in the CES report.24

Statistical analysis

We compared distributions of each individual and neighborhood-level characteristics among patients in the three mutually exclusive hospital categories described above: Kaiser Permanente Northern California, NCICCs, and other non-NCICCs. The census-based neighborhood and environmental pollution attributes were categorized into quartiles (Q1–Q4), based on the population distributions in the study catchment counties. Statistical significance of the difference in distributions between the hospital categories was determined at an alpha level of 0.05 using Chi square tests.

Results

This analysis included 20,178 patients diagnosed with lung cancer from 2015 through 2019, with 30% (n = 6133) from Kaiser Permanente Northern California, 8% (n = 1634) from NCICCs, and 62% (n = 12,411) from other non-NCICCs (Table).

Table Percentage distribution of individual and neighborhood-level characteristics of patients with lung cancer by hospital category; all patients diagnosed with any stage invasive lung cancer 2015–2019, Northern California

Characteristic	Kaiser Permanente Northern California, % (n = 6133)	Non-Kaiser Permanente Northern California	All hospitals, % (N = 20,178)	
NCI-designated cancer centers, % (n = 1634)	All other hospitals, % (n = 12,411)	
Race	
 American Indian	0.7	0.5	0.7	0.7	
 Asian/Pacific Islander	18.0	28.5	20.5	20.4	
 Hispanic	9.4	6.5	10.4	9.8	
 Non-Hispanic Black	8.8	7.6	8.3	8.4	
 Non-Hispanic White	63.1	56.6	59.8	60.5	
 Other/unknown	0.1	0.5	0.3	0.2	
Age at diagnosis (years)	
 < 40	1.1	2.1	0.6	0.9	
 40–49	2.7	3.4	2.3	2.5	
 50–59	11.9	14.1	12.4	12.4	
 60–69	27.9	32.3	30.4	29.8	
 70–79	34.2	31.9	32.5	33.0	
 ≥ 80	22.3	16.4	21.8	21.5	
Sex	
 Male	46.0	52.1	50.5	49.3	
 Female	54.0	47.9	49.4	50.7	
Health insurance status	
 No insurance	0.6	1.0	0.7	0.7	
 Private only	74.0	25.2	20.4	37.1	
 Medicare only or Medicare + private	21.6	42.4	46.4	38.5	
 Any Medicaid	1.5	20.4	24.2	17.0	
 Any military/other public	0.3	9.7	6.1	4.6	
 Unknown	1.9	1.3	2.2	2.0	
AJCC stage at diagnosis	
 I	21.6	30.7	19.2	20.9	
 II	6.2	7.5	6.4	6.4	
 III	17.7	15.2	17.9	17.6	
 IV	51.7	43.0	51.7	51.0	
 Unknown	2.7	3.5	4.8	4.1	
Histologic type (ICD-O-3)	
 Adenocarcinoma	53.8	61.4	51.1	52.7	
 Squamous cell carcinoma	15.8	15.0	18.1	17.1	
 Large cell and other specified carcinoma	7.6	7.3	6.3	6.8	
 Small cell	8.3	5.7	9.9	9.1	
 Unspecified carcinoma	14.7	10.6	14.6	14.3	
Charlson comorbidity score	
 0	14.3	30.5	22.8	20.8	
 1	14.1	22.0	26.8	22.6	
 2	7.7	11.4	15.0	12.5	
 ≥ 3	13.4	12.7	21.9	18.5	
 Unknown	50.6	23.4	13.6	25.6	
History of cigarette smoking	
 Never use	16.6	16.9	13.4	14.7	
 Current use	18.9	14.3	21.9	20.4	
 Former use	42.6	30.2	34.5	36.6	
 Unknown	21.9	38.6	30.2	28.4	
nSES	
 Q 1: low ( < –0.44)	20.2	17.6	30.2	26.1	
 Q 2 (–0.44 to 0.21)	25.9	20.0	25.5	25.2	
 Q 3 (0.22 to 0.90)	27.8	25.8	23.0	24.7	
 Q 4: high ( > 0.90)	26.0	36.2	21.0	23.7	
 Unknown	0.1	0.4	0.3	0.3	
Asian enclave score	
 Q 1: low ( < –0.46)	21.6	17.3	26.7	24.3	
 Q 2 (–0.46 to 0.31)	25.8	22.0	24.1	24.5	
 Q 3 (0.32 to 1.02)	27.9	25.0	23.6	25.0	
 Q 4: high ( > 1.02)	24.6	35.4	25.4	26.0	
 Unknown	0.1	0.4	0.3	0.3	
Hispanic enclave score	
 Q 1: low (score < –0.83)	23.8	25.5	23.1	23.5	
 Q 2 (–0.83 to –0.26)	27.3	28.2	23.0	24.7	
 Q 3 (–0.25 to 0.34)	26.5	24.4	24.5	25.1	
 Q 4: ( > 0.34)	22.3	21.6	29.0	26.4	
 Unknown	0.1	0.4	0.3	0.3	
% Hispanic/Latino population	
 Q 1: low ( < 11.55%)	23.4	35.7	22.2	23.6	
 Q 2 (11.55%–21.18%)	27.1	26.9	23.3	24.8	
 Q 3 (21.19%–34.97%)	28.1	21.1	24.9	25.6	
 Q 4: high ( > 34.97%)	21.2	16.0	29.4	25.9	
 Unknown	0.1	0.4	0.1	0.2	
% non-Hispanic Asian population	
 Q 1: low ( < 4.8%)	21.4	16.4	27.3	24.6	
 Q 2 (4.8%–11.81%)	25.4	20.5	24.3	24.3	
 Q 3 (11.82%–26.47%)	26.8	25.9	23.9	25.0	
 Q 4: high ( > 26.47%)	26.2	36.8	24.4	25.9	
 Unknown	0.1	0.4	0.1	0.2	
% non-Hispanic Black population	
 Q 1: low ( < 0.94%)	21.0	27.5	24.5	23.7	
 Q 2 (0.94%–2.76%)	24.7	27.0	24.5	24.8	
 Q 3 (2.77%–7.29%)	25.7	22.6	25.5	25.3	
 Q 4: high ( > 7.29%)	28.4	22.5	25.3	26.0	
 Unknown	0.1	0.4	0.1	0.2	
% non-Hispanic White population	
 Q 1: low ( < 25.04%)	25.1	23.4	27.9	26.7	
 Q 2 (25.04%–46.16%)	25.5	26.7	25.4	25.6	
 Q 3 (46.17%–65.18%)	25.4	25.6	23.7	24.4	
 Q 4: high ( > 65.18%)	24.0	23.9	22.9	23.3	
 Unknown	0.1	0.4	0.1	0.2	
Population density	
 Q 1: low ( < 869)	23.3	23.1	24.8	24.2	
 Q 2 (869–2,078)	25.1	21.1	24.4	24.4	
 Q 3 (2,079–3,297)	26.8	22.8	24.8	25.2	
 Q 4: high ( > 3,297)	24.8	32.7	25.8	26.0	
 Unknown	0.1	0.4	0.1	0.1	
Rural status	
 Not rural	82.3	83.6	79.8	80.9	
 Partly or all rural	17.6	16.0	20.1	19.0	
 Unknown	0.1	0.4	0.1	0.1	
Pollution burden score (CalEnviroScreen) a	
 Q 1: low ( < 3.67)	28.5	28.0	21.7	24.3	
 Q 2 (3.67–4.52)	25.9	27.4	23.6	24.6	
 Q 3 (4.53–5.45)	24.6	24.5	25.8	25.3	
 Q 4: high ( > 5.45)	20.9	19.8	28.7	25.6	
 Unknown	0.1	0.4	0.1	0.1	
Particulate matter air pollution (PM2.5 μg/m3) a	
 Q 1: low ( < 8.32)	25.3	29.3	22.0	23.6	
 Q 2 (8.32–8.64)	27.0	31.6	23.1	25.0	
 Q 3 (8.65–9.03)	28.4	26.4	24.1	25.6	
 Q 4: high ( > 9.03)	19.2	12.4	30.7	25.7	
 Unknown	0.1	0.4	0.1	0.1	
a Study-specific quartiles for the study catchment area counties and assigned by census tract of residence.

AJCC, American Joint Committee on Cancer; ICD-O-3, International Classification of Diseases for Oncology, third edition; NCI, National Cancer Institute; nSES, neighborhood socioeconomic status; PM2.5, particulate matter ≤2.5 microns in diameter; Q, quartile.

Several differences were noted when comparing demographic and clinical characteristics of patients from Kaiser Permanente Northern California to other non-NCICCs. With respect to race and ethnicity, Kaiser Permanente Northern California had a greater proportion of non-Hispanic White (63.1% vs 59.8%) and Black (8.8% vs 8.3%) patients, but a lower proportion of Asian and Pacific Islander (API; 18.0% vs 20.5%) and Hispanic (7.9% vs 10.4%) patients than other non-NCICCs. Kaiser Permanente Northern California patients were more commonly ≥ 70 years of age (56.5% vs 54.3%) and female (54.0% vs 49.4%). Kaiser Permanente Northern California had a much higher proportion of patients with private insurance (74.0% vs 20.4%) and a lower rate of public insurance usage, including Medicaid, Medicare, and military payers. Kaiser Permanente Northern California patients were slightly more likely to have adenocarcinoma (53.8% vs 51.1%) and slightly less likely to have squamous cell carcinoma (15.8% vs 18.1%). Kaiser Permanente Northern California patients were also less likely to be currently smoking (18.9% vs 21.9%). However, smoking status was unknown for variably large proportions of patients in all three hospital categories, with percentage of missing data ranging from 21.9% at Kaiser Permanente Northern California to 38.6% from NCICCs.

Compared to patients from other non-NCICCs, Kaiser Permanente Northern California patients were less likely to reside in lower socioeconomic status (SES) neighborhoods (Q1: 20.2% vs 30.2%) and more likely to reside in higher SES neighborhoods (Q4: 26.0% vs 21.0%). Additionally, they less frequently resided in the lowest and highest population density neighborhoods. Kaiser Permanente Northern California patients were more likely to reside in neighborhoods with the highest percentage of non-Hispanic White and Black residents, and less likely to reside in neighborhoods with the highest percentage of Hispanic residents, with 22.3% of Kaiser Permanente Northern California patients living in the highest quartile of Hispanic enclaves compared to 29.0% at non-NCICCs. Although Kaiser Permanente Northern California patients were slightly more likely to live in neighborhoods with high Asian concentrations (Q4: 26.2% vs 24.4%), they were not more likely to live in Asian American enclaves (Q4: 24.6% vs 25.4%), which are neighborhoods additionally characterized by more recent immigrants and linguistically isolated households. Finally, Kaiser Permanente Northern California patients more frequently resided in neighborhoods with lower pollution burden scores (Q1: 28.5% vs 21.7%) and PM2.5 levels (Q1: 25.3% vs 22.0%).

NCICC patients differed on many individual and neighborhood characteristics when compared to patients from Kaiser Permanente Northern California and other non-NCICCs. NCICC patients were more likely to be API [28.5% vs 18.0% (Kaiser Permanente Northern California) and 20.5% (other non-NCICCs)] and less likely to be Black, White, or Hispanic. NCICC patients were more frequently < 70 years old [51.9% vs 43.6% (Kaiser Permanente Northern California) and 45.7% (other non-NCICCs)] and male [52.1% vs 46.0% (Kaiser Permanente Northern California) and 50.5% (other non-NCICCs)] and had lower Charlson comorbidity scores. However, California Cancer Registry data on comorbidity status were unavailable for 50.6% of Kaiser Permanente Northern California patients, 23.4% of NCICC patients, and 13.6% of other non-NCICC patients. Additionally, NCICC patients were more likely to have stage I disease [30.7% vs 21.6% (Kaiser Permanente Northern California) and 19.2% (other non-NCICCs)] and less likely to have stage IV disease (43.0% vs 51.7% at both Kaiser Permanente Northern California and other non-NCICCs). There was a much higher proportion of patients with adenocarcinoma at NCICCs [61.4% vs 53.8% (Kaiser Permanente Northern California) and 51.1% (other non-NCICCs)] and a lower proportion with all other histologic types. NCICC patients were most likely to reside in the highest SES neighborhoods [Q4: 36.2% vs 26.0% (Kaiser Permanente Northern California) and 21.0% (other non-NCICCs)] and least likely to reside in the lowest SES neighborhoods [Q1: 17.6% vs 20.2% (Kaiser Permanente Northern California) and 30.2% (other non-NCICCs)]. Finally, NCICC patients were least likely to reside in neighborhoods with the highest pollution burden scores [Q4: 19.8% vs 20.9% (Kaiser Permanente Northern California) and 28.7% (other non-NCICCs)] and PM2.5 levels [Q4: 12.4% vs 19.2% (Kaiser Permanente Northern California) and 30.7% (other non-NCICCs)].

All comparisons reported were statistically different at p < 0.001 using Chi square tests, and these differences remained statistically significant when unknown values were excluded.

Discussion

In this study, the authors compared clinical and demographic characteristics of patients with lung cancer from Kaiser Permanente Northern California, NCICCs, and other non-NCICCs in Northern California. Compared to NCICC patients, Kaiser Permanente Northern California patients were more similar to other non-NCICC patients on most characteristics. As expected, Kaiser Permanente Northern California patients were predominantly privately insured, and public insurance was considerably less common than at NCICCs and other non-NCICC hospitals; proportions of uninsured patients were ≤ 1% in all three hospital categories. Kaiser Permanente Northern California patients, when compared to other non-NCICC patients, were more likely to be Black or White, female, and ≥ 70 years old at diagnosis, and less likely to be Hispanic or API and reside in the lowest SES neighborhoods. Additionally, Kaiser Permanente Northern California patients tended to reside in neighborhoods with higher Black, White, or API populations and lower Hispanic populations. As for environmental exposures, Kaiser Permanente Northern California patients were less likely to live in neighborhoods with the highest pollution burden or PM2.5 levels. Other than insurance status, these differences were modest but statistically significant due to large sample sizes.

On the other hand, NCICC patients were strikingly different from both Kaiser Permanente Northern California and other non-NCICC patients on many clinically relevant variables. Importantly, they were most likely to have characteristics associated with improved lung cancer outcomes, including younger age, lower comorbidity burden, adenocarcinoma histology, higher nSES, localized disease, and API ethnicity.2,15,16,25–30 Additionally, NCICC patients were the least likely to live in the areas with the highest pollution burden or PM2.5 levels, a risk factor for not only lung cancer but also increased mortality in patients both with and without lung cancer.31–36 Despite being predominantly privately insured, Kaiser Permanente Northern California patients comprised 31% of the study population, almost four times greater than that of NCICC patients, and were more representative of the Northern California lung cancer patient population with regard to these important prognostic variables. Compared to NCICCs, lung cancer research findings from Kaiser Permanente Northern California are therefore potentially more generalizable to the overall patient population with lung cancer, including patients of elderly age, lower SES, and higher comorbidity burden who are historically underrepresented at NCICCs, where the greatest volume of published research findings are generated.4,6,9,37

Although evidence suggests that receiving cancer care at an NCICC leads to improved outcomes,38–41 many important patient characteristics have been identified as potential barriers to NCICC access, including increased travel time to an NCICC, higher comorbidity burden, older age, Black or Hispanic race, female sex, and increased neighborhood poverty.37,42 These findings are consistent with those in the present study in showing that NCICC patients in Northern California, when compared to other non-NCICC patients, were more likely to be younger and male, have fewer comorbidities, and come from higher SES neighborhoods. As such, the reported differences in outcomes are likely at least partially attributable to patient selection, especially in California, where NCICCs see < 5% of all patients with cancer.42 On the other hand, integrated health care systems serve a significantly larger patient population with cancer and have been shown to improve cancer mortality and reduce racial disparities in receipt of evidence-based cancer care when compared to nonintegrated health systems.43–45 Consequently, Kaiser Permanente Northern California and similarly large integrated health care systems may represent a preferred setting for research evaluating the diffusion and impact of cancer advances from NCICCs to diverse real-world populations.

As cancer mortality in the United States continues to decrease with improvements in detection and management, the increasing prevalence of cancer survivors will warrant greater emphasis on survivorship care; this includes surveilling for new or recurrent malignancy, managing long-term cancer and cancer treatment-related morbidity, and addressing psychosocial needs.46,47 To this end, survivorship research is key to improving long-term care delivery for these patients. Integrated health care systems, including Kaiser Permanente Northern California, are well positioned to conduct studies on long-term cancer survivorship, as well as on screening and early detection of cancer, because they have high retention rates, with a majority of their patients having been followed for ≥ 10 years both before and after cancer diagnosis,12,13,48 and extensive EHR data.

Although a previous study produced similar conclusions about patients with breast cancer from Kaiser Permanente Northern California,10 the authors are unaware of existing research on the representativeness of lung cancer patients at an integrated health care system compared to NCICCs and the overall patient population. The present study does have several limitations. First, because of the large and variable amounts of smoking data missing from all institutions, the authors were unable to draw meaningful conclusions about tobacco use distributions in this study’s population. Given growing evidence that lung cancer behaves differently in patients with and without tobacco use,49,50 smoking status is an important variable to consider when assessing the generalizability of lung cancer research. Second, the present study focuses on lung cancer at a single, albeit large, integrated health care system in Northern California; as such, this study’s comparisons may not reflect those of different institutions, regions, or diseases. Last, this study’s population was predominantly privately insured, which limits generalizability to publicly insured or uninsured patients. Despite these limitations, the present study provides useful context for interpreting lung cancer research conducted at Kaiser Permanente Northern California and similar integrated health care systems and bolsters the value of such research embedded in integrated health care systems.

In summary, patients with lung cancer from an integrated health care system appear more broadly representative of the underlying lung cancer population than patients from NCICCs. This finding supports that comprehensive, longitudinal EHR data from integrated health care systems are useful in contributing generalizable real-world evidence on lung cancer care.

Author Contributions: Mike Z Yang, MD, and Raymond Liu, MD: Study design and manuscript writing. Julie Von Behren, MPH, and Katherine Lin, MPH: Data analysis and presentation. Scarlett L Gomez, PhD, MPH, and Salma Shariff-Marco, PhD, MPH: Study design and data acquisition. Lori C Sakoda, PhD, MPH: Study design, manuscript writing, and acquisition of funding support. All authors: Critical review and approval of the final manuscript.

Conflicts of Interest: Drs Liu, Velotta, and Sakoda have received research funding from AstraZeneca that was awarded to their institution. Dr Wong reports conflicts of interest outside of this work (royalties from UpToDate; immediate family member is employed by Genentech with stock ownership). An earlier version of an abstract of this work was published for the 2023 American Society for Clinical Oncology (ASCO) Annual Meeting. Copyright for materials presented remains with the authors.

Funding: This work was supported by the National Cancer Institute at the National Institutes of Health (R01 CA263322 to L.C.S.).This work was supported by the National Cancer Institute at the National Institutes of Health (R01 CA263322 to L.C.S.). The funder did not play any role in the study design; data collection, analysis, and interpretation; manuscript writing; and decision to submit the manuscript for publication.

Data-Sharing Statement: Study data can be shared with interested researchers upon request.
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