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Annals of Medicine and Surgery logoLink to Annals of Medicine and Surgery
. 2020 Dec 1;60:680–685. doi: 10.1016/j.amsu.2020.11.081

Gender disparities in lung cancer survival from an enriched Florida population-based cancer registry

Adel Elkbuli a,b,, Margaret M Byrne a,e, Wei Zhao e, Mason Sutherland b, Mark McKenney b,d, Yeissen Godinez c, Devina J Dave a, Layla Bouzoubaa a,e, Tulay Koru-Sengul a,e
PMCID: PMC7723764  PMID: 33318793

Abstract

Background

Previous studies have revealed gender disparities in lung cancer survivorship, but comprehensive inclusion of clinical/individual variables which affect outcomes is underreported. We utilized the Florida Data Cancer System (FCDS) to examine associations between gender and lung cancer survivorship while controlling for prognostic variables on a large population-based scale.

Methods

A retrospective cohort analysis utilizing the FCDS, linked to Florida Agency for Health Care Administration and US Census Bureau tracts for patients diagnosed with primary lung cancer (n = 165,465) from 1996 to 2007. Primary outcome measures included median survival time and mortality. Multivariable Cox regression models, independent sample T-tests, and descriptive statistics were utilized with significance defined as p < 0.05.

Results

165,465 cases were analyzed revealing 44.3% females and 55.7% males. The majority of patients were white/Caucasian, males, middle-high socioeconomic status, lived in urban areas, and geriatric age. Females had longer median survival compared to males (9.6 vs 7.1 months). Multivariable analyses showed that women had better survival after controlling for sociodemographic, clinical, and comorbidity covariates. Males had higher risk of mortality than females (aHR = 1.17, 95%CI 1.14–1.19, p < 0.01).

Conclusions

Individuals of higher socioeconomic status experienced greater survivorship compared to those of lower socioeconomic status. Women experienced significantly better survival for lung cancer at multiple time frames after controlling for covariates compared to men. Interventions aimed at public education and access to high-quality healthcare are needed to ameliorate socioeconomic and gender-based disparities in lung cancer survivorship. Future studies should investigate gender differences in lung cancer while incorporating individual socioeconomic status and treatment received.

Keywords: Lung cancer survival, Health inequalities, Gender disparity, Socioeconomic status, Healthcare access

Highlights

  • Women have a significantly better survival for lung cancer at multiple time frames after controlling for covariates compared to men.

  • The observations of our study shed light on a potential gender gap as well as economic disparities in overall lung cancer survivorship.

  • This data accentuates the importance of focusing future preventative efforts on public education and the access to prompt healthcare in hopes of narrowing survival disparities in lung cancer.

1. Introduction

Cancers of the lung are among the most prevalent malignancies in the United States (US) with adenocarcinoma representing the most common type of lung carcinoma [[1], [2], [3]]. The American Cancer Society estimates that 234,030 new cases of lung cancer occurred in the US in 2018 and 228,150 cases in 2019, leading to 154,050 deaths and 142,670 deaths, respectively [1,2,4]. An interesting disparity reported in previous literature regarding lung cancer is the better survivorship of female patients compared to males [[5], [6], [7], [8], [9], [10], [11]]. According to the National Cancer Institute's Surveillance, Epidemiology, and End Results (NCI-SEER) program, there are 63.5 deaths per 100,000 men compared to 39.2 deaths per 100,000 women of all race/ethnicity groups for cancer of the lung and bronchus, with women diagnosed with small cell lung cancer (SCLC) experiencing a particularly prominent survival advantage [5]. Previous studies utilizing NCI-SEER data from 1975 to 1999 have indicated that although women have a greater incidence of lung cancer compared to men, they also experience higher stage-specific survival rates than male counterparts [[6], [7], [8]]. Univariate and multivariable analyses have demonstrated that female gender is associated with improved lung cancer survivorship, with females diagnosed with non-small cell lung cancer (NSCLC) experiencing greater survivorship compared to males in a phase III Eastern Cooperative Oncology Group (ECOG) trial [[8], [9], [10]].

However, there are numerous influences besides gender which may play a role in the increased survivorship of female patients compared to males including age and smoking history, among other variables [11]. In particular, greater exploration of the impact of relevant socioeconomic and individual factors such as patient race/ethnicity and insurance status has the potential to further explain why female lung cancer patients may experience greater survivorship compared to male counterparts. Therefore, this review aims to utilize the 1996–2017 Florida Cancer Data System (FCDS) registry data enhanced with Florida Agency for Health Care Administration (FL-AHCA) information to assess for potential economic inequalities in survivorship for female lung cancer patients by accounting for patient race/ethnicity, comorbidities, smoking status, insurance status, marital status, hospital characteristics, treatment type, and carcinoma grade with the hypothesis that female lung cancer survivorship is associated with a higher overall socioeconomic status.

2. Material and methods

A retrospective cohort analysis was performed utilizing data from the US Census Bureau, FCDS and FL-AHCA regarding lung cancer incidence and inpatient outpatient procedures to treat lung carcinoma from 1996 to 2007. This report was conducted in line with the STROCSS criteria [12]. The FCDS is a statewide cancer registry funded by the Florida Department of Health (FL-DOH) and the Centers for Disease Control and Prevention's National Program of Cancer Registries (CDC-NPCR) which receives annual information from 252 hospitals, 127 radiation therapy centers, 453 surgery centers, and 3360 physician offices in the state of Florida [13]. We report data in accordance with research agreements with FCDS and utilized one cohort of patients according to FCDS patient inclusion criteria: adult patients who were at least 18 years of age, diagnosed with primary lung cancer, and resided in the state of Florida when diagnosed [13]. Matches between the FCDS and FL-AHCA data were confirmed with the patient's date of birth and gender. Patients were not involved in study design of this analysis.

Survival time was defined as the elapsed time from lung cancer diagnosis to death or last follow-up for alive patients. Patient residency and the year 2000 US Census Bureau information was utilized to approximate the patient's neighborhood socioeconomic status (NSES), defined as the percentage of households living below the federal poverty line: lowest (≥20%), middle-low (≥10% and <20%), middle-high (≥5% and <10%), and highest (<5%). NSES was utilized as previous studies have indicated that this measure yielded similar results to more complex composite scores, with poverty as an ideal indicator because this metric produces similar results to multivariable indices incorporating multiple contributing factors to socioeconomic status such as education and total asset possession [14,15]. Additionally, NSES was utilized over individual socioeconomic status information on the basis that individual SES data was not available in our dataset as well as to account for geographical area-based socioeconomic differences which may have implicit influences on patient health [16].

Multivariable Cox regression models were fitted by including variables of patient race/ethnicity, smoking status, insurance, marital status, hospital characteristics, treatment, cancer stage, cancer grade, and comorbidities in order to examine overall survivorship as the primary clinical outcome. Adjusted hazard ratios (aHRs), corresponding 95% confidence intervals (95% CI), and independent sample T-tests were calculated with significance defined as p < 0.05. Data management and statistical analyses were performed using SAS v9.4 statistical software for Windows (SAS Institute Inc., Cary, NC, USA). This study was conducted in compliance with ethical principles, was reviewed and approved by the FL-DOH and University of Miami institutional review boards. The Research Registry UIN of this study is: researchregistry6293. [17].

3. Results

3.1. Patient characteristics

Our sample initially included information on 179,630 adults ≥18 years of age in the state of Florida diagnosed with SCLC or NSCLC carcinoma-in-situ or higher staging from 1996 to 2007. Of this total, 14,165 patients were excluded on the basis of missing information regarding gender, race/ethnicity, NSES, SEER stage, or survival time, yielding 165,465 patients included in the final dataset. As seen in Table 1, the dataset was comprised of 73,276 (44.3%) female and 92,189 male (55.7%) patients. The majority of patients were white (n = 152,880; 92.4%), non-Hispanic (n = 155,402; 93.9%), most commonly middle-high NSES (n = 61,840; 37.4%), possessed Medicare insurance (55.6%), and were married (53.2%). Most patients lived in urban areas (93.0%), and were treated at low-volume hospitals (64.4%) and non-teaching hospital hospitals (92.6%). The majority of patients had a current or past history of smoking (73.3%). Females comprised a larger proportion of the never-smoker group (n = 8677; 11.8%) compared to males (n = 5666; 6.1%). Both male and female patient populations were comprised of primarily geriatric individuals (age ≥ 65) [Table 1]. There was no significant difference in mean age at time of cancer diagnosis between males and females (70.1 years vs. 69.5 years, p > 0.05). In addition, the median age at diagnosis was similar for both genders at 71.0 years (male interquartile range [IQR] = 15 years, female IQR = 14 years).

Table 1.

Demographic characteristics of lung cancer by gender.

Variable All patients
Female
Male
N % N % N %
All patients 165,465 100.0 73,276 100.0 92,189 100.0
Race
White 152,880 92.4 68,562 93.6 84,318 91.5
Black 11,462 6.9 4165 5.7 7297 7.9
NA 57 0.0 16 0.0 41 0.0
Asian 526 0.3 275 0.4 251 0.3
PI 45 0.0 23 0.0 22 0.0
AIP 115 0.1 51 0.1 64 0.1
Other 380 0.2 184 0.3 196 0.2
Hispanic Origin
Non-Hispanic 155,402 93.9 69,770 95.2 85,632 92.9
Hispanic 10,063 6.1 3506 4.8 6557 7.1
NSES
Lowest 21,406 12.9 8423 11.5 12,983 14.1
Middle-Low 53,742 32.5 22,866 31.2 30,876 33.5
Middle-High 61,840 37.4 28,625 39.1 33,215 36.0
Highest 28,477 17.2 13,362 18.2 15,115 16.4
Vital status (not in model)
Alive
22,437 13.6 12,248 16.7 10,189 11.1
Dead 143,028 86.4 61,028 83.3 82,000 88.9
Age at diagnosis (years)
Mean (SD) 69.7 (11.2) 69.5 (10.9) 70.1 (11.5)
Median (Q1, Q3) 71.0 (63.0,78.0) 71.0 (63.0,77.0) 71.0 (63.0,78.0)
Min, Max 18.0, 110.0 18.0, 105.0 18.0, 110.0
Tobacco Use
Never 14,343 8.7 8677 11.8 5666 6.1
History 65,651 39.7 27,161 37.1 38,490 41.8
Current 55,678 33.6 24,543 33.5 31,135 33.8
Unknown 29,793 18.0 12,895 17.6 16,898 18.3
Marital Status
Never Married 20,528 12.4 7233 9.9 13,295 14.4
Divorced/Separated/Widowed 52,655 31.8 33,492 45.7 19,163 20.8
Married 88,045 53.2 30,661 41.8 57,384 62.2
Unknown 4237 2.6 1890 2.6 2347 2.5
Insurance Status
Uninsured 5663 3.4 2188 3.0 3475 3.8
Private Insurance 31,018 18.7 14,251 19.4 16,767 18.2
Medicaid 5938 3.6 2423 3.3 3515 3.8
Medicare 92,011 55.6 41,667 56.9 50,344 54.6
Defense/Military/Veteran 2482 1.5 679 0.9 1803 2.0
Indian/Public 225 0.1 105 0.1 120 0.1
Insurance, NOS 10,803 6.5 4940 6.7 5863 6.4
Unknown 17,325 10.5 7023 9.6 10,302 11.2
Urban Rural by zip code
Urban 153,829 93.0 68,802 93.9 85,027 92.2
Rural 11,636 7.0 4474 6.1 7162 7.8
AAMC 2005 Teaching Hospital
Non-teaching hospital 153,145 92.6 67,958 92.7 85,187 92.4
Teaching hospital 12,320 7.4 5318 7.3 7002 7.6
Hospital Volume
Low 106,496 64.4 47,056 64.2 59,440 64.5
High 58,969 35.6 26,220 35.8 32,749 35.5

Race abbreviations are as follows: NA=Native American, PI=Pacific Islander, AIP = Asian Indian or Pakistani; NSES: percentage of households living below the federal poverty line: lowest (≥20%), middle-low (≥10% and <20%), middle-high (≥5% and <10%), and highest (<5%); SD: standard deviation.

3.2. Clinical and pathological characteristics

Lung carcinomas were most commonly graded as poorly differentiated (23.0%), with more males (24.0%) than females (21.7%) being diagnosed with this grade [Table 2]. The predominant histological type of the tumors was adenocarcinoma (27.7%), comprising 25.0% of lung malignancies in males and 31.0% of lung malignancies in females. More male patients (20.6%) were diagnosed with squamous cell cancer (SCC)/combine complex than females (14.2%). The most common treatment received by patients was radiotherapy (39.3%), followed by chemotherapy (31.6%), and surgery (21.6%).

Table 2.

Pathological and clinical characteristics.

Variable All patients
Female
Male
N % N % N %
All 165,465 100.0 73,276 100.0 92,189 100.0
Co-morbidity
None 13,699 8.3 5337 7.3 8362 9.1
1–2 5910 3.6 2662 3.6 3248 3.5
3–4 12,702 7.7 6015 8.2 6687 7.3
>4 133,154 80.5 59,262 80.9 73,892 80.2
SEER Stage
Localized 27,347 16.5 13,621 18.6 13,726 14.9
Regional, direct extension ± lymph nodes 19,960 12.1 8699 11.9 11,261 12.2
Regional, lymph nodes only 14,142 8.5 6365 8.7 7777 8.4
Distant 66,028 39.9 28,354 38.7 37,674 40.9
Unknown/Unstaged 37,988 23.0 16,237 22.2 21,751 23.6
Types of lung cancer
SCLC 20,593 12.4 9874 13.5 10,719 11.6
NSCLC 98,541 59.6 43,338 59.1 55,203 59.9
Other 46,331 28.0 20,064 27.4 26,267 28.5
Grade
Undifferentiated 12,125 7.3 5457 7.4 6668 7.2
Poorly-differentiated 38,048 23.0 15,884 21.7 22,164 24.0
Moderately-differentiated 18,916 11.4 8570 11.7 10,346 11.2
Well-differentiated 5794 3.5 3053 4.2 2741 3.0
Unknown/not stated 90,582 54.7 40,312 55.0 50,270 54.5
Regional Nodes Positive
No 20,141 12.2 9810 13.4 10,331 11.2
Yes 11,890 7.2 5367 7.3 6523 7.1
Unknown 133,434 80.6 58,099 79.3 75,335 81.7
Histologic Type
Adenocarcinoma 45,808 27.7 22,750 31.0 23,058 25.0
Squamous/combine complex 29,336 17.7 10,382 14.2 18,954 20.6
Neuroendocrine 2580 1.6 1523 2.1 1057 1.1
Large cell 7936 4.8 3284 4.5 4652 5.0
Other 15,424 9.3 6690 9.1 8734 9.5
Unknown 64,381 38.9 28,647 39.1 35,734 38.8
Chemotherapy
No 95,994 58.0 43,368 59.2 52,626 57.1
Yes 52,305 31.6 22,954 31.3 29,351 31.8
Unknown 17,166 10.4 6954 9.5 10,212 11.1
Radiation Therapy
No 87,238 52.7 40,605 55.4 46,633 50.6
Yes 65,028 39.3 27,424 37.4 37,604 40.8
Unknown 13,199 8.0 5247 7.2 7952 8.6
Surgery
No 117,283 70.9 51,254 69.9 66,029 71.6
Yes 35,725 21.6 17,087 23.3 18,638 20.2
Unknown 12,457 7.5 4935 6.7 7522 8.2

SCLC = small cell lung cancer, NSCLC = non-small cell lung cancer.

3.3. Association between survival and gender

Median survival time (MST) increased accordingly by NSES level [Table 3]. A longer MST was observed for female patients than male patients (9.6 months vs. 7.1 months) (p < 0.001). Survival rates were also higher in females compared to male patients at 1, 3, and 5 years after diagnosis as demonstrated in Fig. 1 (p < 0.001). Multivariable analyses demonstrated that women had better survival than men after controlling for race/ethnicity, NSES, and other sociodemographic/clinical/comorbidity covariates [Table 4 & Fig. 1]. In our fully adjusted model, males had higher risk of mortality than females (aHR = 1.17, 95% CI: 1.14–1.19, p < 0.01). No significant interactions between gender, race/ethnicity, and NSES were detected in fully adjusted models.

Table 3.

Median and survival rates, n = 165,465.


Median survival (months)
Survival rates (%) at time (years) after diagnosis
1 year 3 years 5 years
Overall 8.1 39.9 18.2 12.0
Gender
Female 9.6 44.4a 21.9a 15.0a
Male 7.1 36.4a 15.3a 9.7a
Raceb
White 8.1 40.2 18.5 12.3
Black 7.0 36.2 14.4 8.8
NA 4.8 36.5 9.8 4.9
Asian 10.8 45.8 20.9 12.3
PI 12.9 51.3 21.6 10.3
AIP 11.0 48.0 21.5 12.4
Other 8.9 44.6 18.4 13.0
Hispanic Origin
No 8.0 39.9 18.2 12.0
Yes 8.4 40.5 17.9 12.0
NSES
Lowest 6.5 34.8 13.7 8.6
Middle-low 7.6 38.4 16.8 11.0
Middle-high 8.5 41.2 19.4 12.8
Highest 9.6 44.0 21.7 15.0
a

Females possessed significantly higher survival rates than males at the 1, 3, and 5 year time points after diagnosis (p < 0.001).

b

Race abbreviations are as follows: NA=Native American, PI=Pacific Islander, AIP = Asian Indian or Pakistani; NSES: Neighborhood Socioeconomic Status; Lowest (≥20%); Middle-Low (≥10% and <20%); Middle-High (≥5% and <10%); Highest (<5%).

Fig. 1.

Fig. 1

Survival Plots (a) Gender (b) Race (c) Hispanic or non-Hispanic (d) NSES: L = Lowest (≥20%), ML = Middle-Low (≥10% and <20%), MH = Middle-High (≥5% and <10%), and H = highest (<5%) NSES.

Table 4.

Cox Regression Models for Overall Survival Clustered Hospital, n = 165,465.

Prognostic factors Category Model 1
Model 2
HR (95%CI) P value aHR (95%CI) P value
Gender Female 1.00 1.00
Male 1.23 (1.22,1.25) <0.001 1.17 (1.14,1.19) <0.001
Race White 1.00 1.00
Black 1.12 (1.10,1.15) <0.001 0.98 (0.95,1.02) 0.314
NA 1.39 (1.04,1.85) 0.024 1.17 (0.92,1.50) 0.196
Asian 0.88 (0.80,0.97) 0.012 0.87 (0.79,0.97) 0.010
PI 0.83 (0.59,1.16) 0.268 0.75 (0.50,1.12) 0.162
AIP 0.86 (0.70,1.06) 0.168 0.97 (0.80,1.17) 0.727
Other 0.95 (0.84,1.07) 0.386 0.94 (0.83,1.07) 0.342
Hispanic No 1.00 1.00
Yes 0.99 (0.96,1.01) 0.205 0.94 (0.89,0.99) 0.015
NSES Lowest 1.00 1.00
Middle-Low 0.90 (0.89,0.92) <0.001 0.96 (0.93,0.98) 0.001
Middle-High 0.84 (0.82,0.85) <0.001 0.92 (0.89,0.94) <0.001
Highest 0.77 (0.76,0.79) <0.001 0.88 (0.84,0.91) <0.001

Model 1: Univariate.

Model 2: Multivariate - gender + Race/Ethnicity/SES + demographics + clinical + comorbidities (use individual variables).

aHR = Adjusted Hazard Ratio; 95%CI = 95% Confidence Interval.

None of the models included interaction terms. There are no significant interactions between gender and race, ethnicity, and NSES respectively in model 5. Race abbreviations are as follows: NA=Native American, PI=Pacific Islander, AIP = Asian Indian or Pakistani; NSES: Neighborhood Socioeconomic Status (living below poverty line); Lowest (≥20%); Middle-Low (≥10% and <20%); Middle-High (≥5% and <10%); Highest (<5%).

4. Discussion

It was found that the majority of adult patients who were diagnosed with primary lung carcinoma in the state of Florida from 1996 to 2007 where white/Caucasian, males, middle-high NSES, lived in urban areas, and were of a geriatric age. Poorly differentiated adenocarcinoma was the most common type of lung malignancy diagnosed, with the most frequently received treatments being radiotherapy, followed by chemotherapy and surgery. Women experienced significantly greater 1-, 3-, and 5-year survivorship compared to men after controlling for race, ethnicity, NSES, sociodemographic, clinical, and comorbidity covariates.

Our study indicates that when controlling for known prognostic factors such as patient medical comorbidities and smoking status, NSES exerted a significant impact on lung cancer survivorship, with both male and female patients of a higher NSES experiencing greater survivorship compared to more socioeconomically disadvantaged counterparts. These findings are supported by previous literature and may be due to the influence of multiple factors including a greater ability of higher NSES patients to access and receive high quality care and ancillary services throughout the duration of their treatment, as well as a greater amount of health literacy and knowledge regarding lung cancer diagnoses and treatment [[18], [19], [20]]. Critical to the discussion of socioeconomic status on the survivorship of lung cancer patients is the type of insurance possessed by patients. Previous studies have shown that higher quality insurance is associated with greater detection and treatment of early-stage lung carcinomas [21]. Given the mixed conclusions regarding the impact of insurance type on treatment complications, hospital duration of stay, and mortality of lung carcinoma patients, the benefit of possessing comprehensive insurance by higher-NSES individuals may stem from early disease detection and management more than the modality or duration of treatment received [21,22]. The implications of these findings are that socioeconomically disadvantaged cancer patients may benefit from greater implementation of interventions aimed at improving their access to high quality healthcare, as well as additional efforts aimed at improving education regarding the importance of screening and early symptoms to ameliorate any disparity conferred by unfavorable insurance coverage [23,24].

However, our findings also indicate that after controlling for relevant covariates, women of higher NSES have a significantly higher lung cancer survival rate compared to male counterparts at multiple time frames post-diagnosis and further substantiates previous literature which have implicated a gender disparity in lung cancer survivorship between women and men [25,26]. The evaluation of both intrinsic and extrinsic confounders is necessary in order to further delineate these gender disparities. Our findings that women comprised the majority of patients who have never used tobacco products and developed adenocarcinoma is supported by previous literature and highlights a possible predilection for this gender to develop adenocarcinoma in comparison to males, possibly due to the greater influence of endogenous and exogenous estrogens and progestins, as well as a greater frequency of mutations in the tumor suppressor gene p53 and proto-oncogene K-RAS [[27], [28], [29]]. This greater risk for women to develop lung carcinoma is compounded when the influence of tobacco is introduced [29]. However, the higher survivorship observed for female patients of higher-NSES in our study may indicate that although the incidence of lung cancer is higher among women, an increased willingness to seek medical attention and utilize necessary services aimed at improving morbidity and mortality may be a considerable influence in these individuals experiencing greater survivorship [30].

Our study design offers several advantages compared to prior studies. While several previous investigations have described gender-related differences in lung cancer survivorship, ours confers an advantage over other studies by adjusting for relevant covariables in our Cox regression model such as insurance status, race/ethnicity, and age, among others [31]. Therefore, the results of our study allow for a greater degree of generalizability as the racial/ethnic, and geographic distribution of patients in the FCDS, FL-AHCA, and US Census Bureau from 1996 to 2007 do not significantly deviate from the national population of lung cancer patients and incorporate data from hundreds of medical centers rather than single center studies [31]. However, there are several limitations to our study. First, our investigation was subject to inherent limitations of retrospective analyses including selection bias and retention of subjects to follow-up which may have affected certain variables in our analysis, such as median survival time. Relatedly, analysis of retrospective data was reliant on accurate data entry and could be subject to human error. As such, approximately 10% of patients who satisfied our inclusion criteria were excluded on the basis of missing or insufficient data. Secondly, NSES was used as a proxy for individual level socioeconomic status and therefore may over- or underestimate trends for patients of an individual socioeconomic status which significantly differs from their NSES. Thirdly, our regression models do not account for the duration or type of treatment (radiation, chemotherapy, surgery, or combination therapy) which can serve as potential cofounders on overall survival.

We hypothesized that female lung cancer survivorship is associated with a higher socioeconomic status. Our findings that after controlling for relevant confounders, individuals of higher NSES experienced higher cancer survivorship compared to individuals of lower NSES, as well as women of higher NSES experiencing greater survivorship compared to males of higher NSES, support our hypothesis and validate previous literature which detail gender-related differences in long-term survival [18]. However, given the multifactorial contributions of individual, institutional, and systematic influences on lung cancer survivorship, we recommend for future studies to investigate the impact different of gender on lung cancer survivorship while incorporating individual socioeconomic status and type/duration of treatment received in order to further investigate potential gender-related differences and develop targeted interventions. Relatedly, we recommend for future studies to include information regarding patient medications and follow-up setting, duration, and frequency alongside outcomes in order to examine the impact of these aspects of clinical care on lung cancer survivorship. Specific efforts which may serve to benefit socioeconomically disadvantaged cancer patients may be greater access to affordable public insurance policies and more robust educational interventions aimed at explaining the importance of lung cancer screening, early detection, and treatment compliance. Greater elaboration of the variables which may be contributing the socioeconomic and gender-based differences observed in this analysis can serve to improve lung cancer patient outcomes for all affected members of the US population.

5. Conclusion

Individuals of higher NSES diagnosed with primary lung cancer in the state of Florida from 1996 to 2007 had a significantly higher survivorship at multiple time points compared to socioeconomically disadvantaged populations, highlighting socioeconomic disparities in survivorship. Additionally, women diagnosed with primary lung cancer experienced significantly higher survivorship compared to men, highlighting a potential gender disparity. This data accentuates the importance of focusing future preventative efforts on public education and the access to prompt healthcare in hopes of narrowing survival disparities in lung cancer.

Sources of funding

Funding and Disclosures: This work was funded by James and Esther King Florida Biomedical Research Program (#10KG-06). The authors confirm that the funder had no influence over the study design, content of the article, or selection of this journal. The authors have no conflicts to report. All authors have no disclosures or conflicts to report.

Ethical approval

This study was conducted in compliance with ethical principles, was reviewed and approved by the FL-Department of Health and University of Miami institutional review boards.

Trial registry number

Researchregistry6293.

If you are submitting an RCT, please state the trial registry number – ISRCTN: Not applicable.

Author contribution

Study design and conception: MB, AE, TS.

Data acquisition, collection, analysis and interpretation: TS, MB, WZ, MS, AE.

Manuscript preparation: AE, MB, WZ, MS, MM, YG, DD, LB, TS.

Critical revision of manuscript: AE, MB, WZ, MS, MM, YG, DD, LB, TS.

Guarantor

Adel Elkbuli.

Tulay Koru-Sengul.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Declaration of competing interest

None.

Footnotes

The abstract leading to this manuscript was presented at the 142ndAmerican Public Health Association (APHA) Annual Meeting in New Orleans, LA, USA.

Appendix B

Supplementary data related to this article can be found at https://doi.org/10.1016/j.amsu.2020.11.081.

Abbreviations

Florida Cancer Data System

FCDS

Adjusted hazard ratios

aHRs

95% Confidence Intervals

95% CI

United States

US

National Cancer Institute's Surveillance, Epidemiology, and End Results

NCI-SEER

Small Cell Lung Cancer

SCLC

Non Small Cell Lung Cancer

NSCLC

Eastern Cooperative Oncology Group

ECOG

Florida Agency for Health Care Administration

FL-AHCA

Socioeconomic Status

SES

Neighborhood Level Socioeconomic Status

NSES

Florida Department of Health

FL-DOH

Centers for Disease Control and Prevention's National Program of Cancer Registries

CDC-NPCR

SD

Standard Deviation

Squamous Cell Cancer

SCC

Median Survival Time

MST

HR

Hazard Ratio

Vitamins and Lifestyle Study

VITAL study

Society of Thoracic Surgeons

STS

Appendix B. Supplementary data

The following is the supplementary data related to this article:

Multimedia component 1
mmc1.docx (31.1KB, docx)

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