Abstract
Chien-Hua Tseng1,2,*, Chun-Ju Chiang2,3,*, Jeng-Sen Tseng4,5, Tsung-Ying Yang4,5, Kuo-Hsuan Hsu6,7, Kun-Chieh Chen4, Chih-Liang Wang8,9, Chih-Yi Chen10,11, Sang-Hue Yen12, Chun-Ming Tsai13, Ming-Shyan Huang14,15, Chao-Chi Ho16, Chong-Jen Yu16,17, Ying-Huang Tsai18,19,20, Jin-Shing Chen17,21,22, Teh-Ying Chou13,23, Ming-Hsun Tsai2,3, Hsuan-Yu Chen24, Kang-Yi Su25,26, Jeremy J.W. Chen7, Huei-Wen Chen27, Sung-Liang Yu25,26,28,29,30, Tsang-Wu Liu31 and Gee-Chen Chang4,5,7,*
1Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan
2Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
3Taiwan Cancer Registry, Taipei, Taiwan
4Division of Chest Medicine, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
5Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan
6Division of Critical Care and Respiratory Therapy, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
7Institute of Biomedical Sciences, National Chung Hsing University, Taichung, Taiwan
8Department of Thoracic Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan
9College of Medicine, Chang Gung University, Taoyuan, Taiwan
10Department of Surgery, Chung Shan Medical University Hospital, Taichung, Taiwan
11Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
12Department of Oncology, Taipei Veterans General Hospital, Taipei, Taiwan
13Division of Thoracic Oncology, Department of Chest Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
14Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
15School of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
16Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
17College of Medicine, National Taiwan University, Taipei, Taiwan
18Department of Pulmonary and Critical Care Medicine, Chiayi Chang Gung Memorial Hospital, Chang Gung Medical Foundation, Puzi, Taiwan
19Department of Respiratory Therapy, Chang Gung University, Taoyuan, Taiwan
20Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
21Division of Thoracic Surgery, Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan
22Department of Traumatology, National Taiwan University Hospital, Taipei, Taiwan
23Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
24Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
25Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan
26Department of Laboratory Medicine, National Taiwan University Hospital, Taipei, Taiwan
27Graduate Institute of Toxicology, College of Medicine, National Taiwan University, Taipei, Taiwan
28NTU Center for Genomic Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
29Department of Pathology, Graduate Institute of Pathology, College of Medicine, National Taiwan University, Taipei, Taiwan
30Center for Optoelectronic Biomedicine, College of Medicine, National Taiwan University, Taipei, Taiwan
31Institute of Cancer Research, National Health Research Institutes, Miaoli, Taiwan
*These authors contributed equally to this work as co-first authors
Correspondence to:
Gee-Chen Chang, email: [email protected]
Keywords: smoking, lung adenocarcinoma, epidermal growth factor receptor (EGFR) mutation, overall survival
Received: June 15, 2017 Accepted: September 24, 2017 Published: October 12, 2017
ABSTRACT
Purpose: In the current targeted therapy era, information on the effect of smoking in epidermal growth factor receptor (EGFR)-mutant lung cancer patients is scarce.
Results: In total, 11,678 adenocarcinoma patients were enrolled. Of these, 33.3% and 91.8% of male and female patients were non-smokers, respectively. An increased amount of smoking (P < 0.001 for trend), fewer smoke-free years (P < 0.001 for trend), and younger age of smoking initiation (P = 0.034 for trend) were all associated with significantly lower EGFR mutation rates. Smokers had a shorter median overall survival (OS) among both EGFR-mutant and EGFR-wild type patients (17.8 vs. 21.1 months, and 7.9 vs. 11.4 months respectively; both P < 0.001). Among patients with EGFR-mutant adenocarcinoma, younger smokers were associated with shorter OS (P = 0.047). In multivariate analysis, female gender was an independent prognostic factor for OS (hazard ratio: 0.86 [95% confidence interval {CI}: 0.80–0.93]; P < 0.001 in the EGFR-mutant group and 0.88 [95% CI: 0.81–0.96]; P = 0.004 in the EGFR-wild type group).
Materials and Methods: We reviewed the National Lung Cancer database (Taiwan) to assess the impact of smoking on the EGFR mutation rate and survival in advanced lung adenocarcinoma patients during 2011 and 2014 retrospectively.
Conclusions: Smoking was associated with lower incidence of EGFR mutation rate and reduced OS of advanced lung adenocarcinoma patients in a dose-dependent manner. In addition to EGFR mutation and smoking, gender also plays an important role in survival among these patients.
INTRODUCTION
Lung cancer is the leading cause of cancer-related death worldwide [1]. Cigarette smoking remains a major risk factor for lung cancer [2]. Moreover, smoking status influences the histological types [3], genotypes [4, 5], and outcomes of lung cancer patients [6].
The epidermal growth factor receptor (EGFR) mutation is one of the most prevalent genetic alterations in lung cancer patients [4, 7]. EGFR-tyrosine kinase inhibitors (TKIs) offer better efficacy and quality of life for lung cancer patients [8, 9], and have hence emerged as an important frontline therapy for patients with EGFR-mutant, non-small cell lung cancer [10].
Previous studies have identified smoking status as a poor prognostic factor in lung cancer [6, 11]. However, in the current era of targeted therapy, limited information is available regarding whether the effects of smoking are similar in patients with different EGFR genotypes. Here, we assessed the National Lung Cancer database from the Taiwan Cancer Registry from 2011 to 2014 to investigate the impact of the smoking status on the EGFR mutation rate and the survival time of advanced lung adenocarcinoma patients.
RESULTS
Patients
Of 45,055 patients with newly diagnosed lung cancer in Taiwan from 2011 to 2014, 37,961 (84.3%) had detailed data for smoking history. Among these patients, 19,685 (51.9%) were non-smokers, and adenocarcinoma was the most common histological type (64.7%). In particular, 33.3% male adenocarcinoma and 91.8% female adenocarcinoma patients were non-smokers. Among the patients with lung adenocarcinoma, 14,654 (59.7%) exhibited advanced stage diseases, and 79.7% of these patients had available EGFR mutation data. A total of 11,678 patients were enrolled for survival analysis (Supplementary Figure 1).
The patient characteristics of the study population are shown in Table 1. In brief, 6,489 patients (55.6%) were female and 8,150 patients (69.8%) were non-smokers. The mean age was 65.9 ± 12.8 years. At the time of lung cancer diagnosis, 93.3% of the patients had stage IV disease and 76.8% of the patients had an ECOG performance status of 0–2. The overall EGFR mutation rate was 61.5%, and the median OS was 16.0 months (95% CI, 15.6–16.4).
Table 1: Demographic and clinical characteristics of the patients
Patient characteristics | N = 11678 |
---|---|
Age, mean (SD), years | 65.9 (12.8) |
Gender, no. (%) | |
Male | 5,189 (44.4) |
Female | 6,489 (55.6) |
Smoking status, no. (%) | |
Non-smokers | 8,150 (69.8) |
Smokers | 3,528 (30.2) |
ECOG performance status, no. (%) | |
0–2 | 8,965 (76.8) |
3–4 | 786 (6.7) |
Unknown | 1,927 (16.5) |
Tumor stage, no. (%) | |
IIIB | 787 (6.7) |
IV | 10,891 (93.3) |
EGFR mutation status, no. (%) | |
Mutant | 7,179 (61.5) |
Wild type | 4,499 (38.5) |
ECOG, Eastern Cooperative Oncology Group; EGFR, epidermal growth factor receptor.
Smoking status and EGFR mutation prevalence
The impact of smoking on the EGFR mutation rate is shown in Table 2. The EGFR mutation rates among smokers and non-smokers were 41.9% and 70.0%, respectively (odds ratio [OR], 0.31 [95% CI, 0.28–0.34]; P < 0.001). In the multivariate analysis, which was adjusted for age, gender, and tumor stage, smoking remained an independent predictor of a lower EGFR mutation rate (adjusted odds ratio [aOR], 0.38 [95% CI, 0.34–0.42]; P < 0.001).
Table 2: Impact of smoking on the EGFR mutation rate
No. | EGFR-m | OR | aOR | P valueb | |
---|---|---|---|---|---|
(%) | (95% CI) | (95% CI)a | |||
Total | 11,678 | 61.5 | - | - | - |
Smoking status | |||||
Non-smokes | 8,150 | 70.0 | Ref. | Ref. | < 0.001 |
Smokers | 3,528 | 41.9 | 0.31 (0.28–0.34) | 0.38 (0.34–0.42) | |
Smoking: pack-year (s) | |||||
> 0–15 | 652 | 51.1 | 0.45 (0.38–0.53) | 0.54 (0.46–0.64) | < 0.001 |
> 15–30 | 1,025 | 44.1 | 0.34 (0.30–0.39) | 0.42 (0.36–0.49) | |
> 30–45 | 651 | 40.9 | 0.30 (0.25–0.35) | 0.37 (0.31–0.45) | |
> 45 | 1,200 | 35.5 | 0.24 (0.21–0.27) | 0.30 (0.26–0.38) | |
Smoke-free year (s) | |||||
> 15 | 349 | 53.3 | 0.49 (0.39–0.61) | 0.63 (0.50–0.79) | < 0.001 |
> 5–15 | 390 | 46.2 | 0.37 (0.30–0.45) | 0.47 (0.38–0.59) | |
> 0–5 | 753 | 42.9 | 0.32 (0.28–0.38) | 0.41 (0.35–0.48) | |
0 (current smokers) | 2,036 | 38.7 | 0.27 (0.25–0.30) | 0.34 (0.30–0.38) | |
Smoking initiation (y/o) | |||||
> 30 | 1,051 | 44.1 | 0.34 (0.30–0.39) | 0.42 (0.36–0.48) | 0.034 |
> 20–30 | 1,377 | 41.9 | 0.31 (0.28–0.35) | 0.39 (0.34–0.45) | |
≤ 20 | 1,100 | 39.6 | 0.28 (0.25–0.32) | 0.36 (0.31–0.41) |
EGFR-m, epidermal growth factor receptor-mutant; OR, odds ratio; aOR, adjusted odds ratio; Ref., reference.
aAdjusted for age, gender, and tumor stage: Non-smokers as a reference group.
bCochran-Mantel-Haenszel test for trends: Lowest level of smoking status as a reference group.
With regard to the amount of smoking, the EGFR mutation rates of patients smoking for > 0–15, > 15–30, > 30–45, and > 45 pack-years were 51.1%, 44.1%, 40.9%, and 35.5%, respectively. Even in patients smoking for < 15 pack-years, the EGFR mutation rate was still significantly lower than that of the non-smokers (aOR, 0.54 [95% CI, 0.46–0.64]; P < 0.001). A significant relationship was observed between an increased amount of smoking and the EGFR mutation rate decline (P < 0.001 for trend). Moreover, similar trends were observed for the number of smoke-free years and the age of smoking initiation, wherein a larger number of smoke-free years and a later age of smoking initiation were associated with a higher EGFR mutation rate (P < 0.001 and 0.034 for trend, respectively).
Smoking status and its impact on survival
The adverse effects of smoking on the survival duration are shown in Figure 1 and Table 3. In the entire population, smokers had a significantly lower OS rate than non-smokers (11.0 months [95% CI, 10.6–11.7] vs. 18.2 months [95% CI, 17.7–18.8]; P < 0.001). As the EGFR mutation status guides distinct treatments and consequently leads to diverse outcomes, we assessed the impact of smoking on patients with different EGFR genotypes. In the present study, patients with EGFR mutations had a longer survival duration than EGFR-wild type patients (20.3 months [95% CI, 19.7–20.9] vs. 9.6 months [95% CI, 9.1–10.0]; HR: 0.56 [95% CI, 0.53–0.58]; P < 0.001). Smokers had a significantly shorter OS among both the EGFR-mutant and EGFR-wild type patients (smokers vs. never-smokers: 17.8 vs. 21.1 months; HR: 1.20 [95% CI, 1.10–1.30]; and 7.9 vs. 11.4 months; HR: 1.33 [95% CI, 1.23–1.47], respectively; both P < 0.001).
Figure 1: Duration of overall survival according to the subgroup with or without smoking. Kaplan-Meier estimates of the duration of overall survival in all advanced lung adenocarcinoma cases (Panel A), in patients with EGFR-wild type (Panel B), and in patients with EGFR mutation (Panel C) are shown. CI, confidence interval.
Table 3: Impact of smoking on the overall survival of patients with advanced lung adenocarcinoma
EGFR-mutant | EGFR-wild type | |||||||
---|---|---|---|---|---|---|---|---|
No. | Median OS | Hazard ratioa | P valueb | No. | Median OS | Hazard ratioa | P valueb | |
(95% CI) | (95% CI) | (95% CI) | (95% CI) | |||||
Total | 7,179 | 20.3 (19.7–20.9) | - | - | 4,499 | 9.6 (9.1–10.0) | - | - |
Smoking status | ||||||||
Non-smokers | 5,702 | 21.1 (20.5–21.8) | Ref. | < 0.001 | 2,448 | 11.4 (10.7–12.2) | Ref. | < 0.001 |
Smokers | 1,477 | 17.8 (16.3–18.7) | 1.20 (1.10–1.30) | 2,051 | 7.9 (7.4–8.5) | 1.33 (1.23–1.47) | ||
Smoking: pack-year (s) | ||||||||
> 0–15 | 333 | 19.5 (17.8–22.4) | 1.10 (0.95–1.26) | 0.007 | 319 | 8.7 (7.2–10.8) | 1.24 (1.08–1.42) | 0.009 |
> 15–30 | 452 | 19.7 (17.0–21.2) | 1.18 (1.04–1.36) | 573 | 8.8 (7.6–9.9) | 1.35 (1.21–1.52) | ||
> 30–45 | 226 | 17.5 (15.1–19.5) | 1.20 (1.02–1.40) | 314 | 8.7 (7.2–10.2) | 1.34 (1.17–1.52) | ||
> 45 | 466 | 13.5 (12.0–15.4) | 1.36 (1.19–1.54) | 845 | 6.0 (5.2–7.7) | 1.49 (1.34–1.66) | ||
Smoke-free year (s) | ||||||||
> 15 | 186 | 16.9 (14.5–18.9) | 1.07 (0.89–1.28) | 0.003 | 163 | 7.5 (5.4–10.2) | 0.94 (0.77–1.12) | 0.002 |
> 5–15 | 180 | 19.0 (14.7–21.8) | 0.96 (0.79–1.15) | 210 | 7.1 (5.3–8.7) | 1.47 (1.15–1.59) | ||
> 0–5 | 323 | 19.3 (17.9–21.9) | 1.15 (0.99–1.32) | 430 | 7.9 (6.8–9.0) | 1.39 (1.22–1.57) | ||
0 (current smokers) | 788 | 16.3 (14.7–17.9) | 1.33 (1.20–1.47) | 1,248 | 8.1 (7.5–8.8) | 1.41 (1.29–1.55) | ||
Smoking initiation (y/o) | ||||||||
> 30 | 464 | 16.8 (15.1–18.9) | 1.08 (0.98–1.26) | 0.047 | 587 | 6.1 (5.2–7.2) | 1.41 (1.26–1.57) | 0.378 |
> 20–30 | 577 | 18.6 (16.6–20.6) | 1.23 (1.09–1.37) | 800 | 8.2 (7.3–9.0) | 1.36 (1.22–1.51) | ||
≤ 20 | 436 | 17.0 (14.5–18.9) | 1.32 (1.16–1.50) | 664 | 9.1 (8.1–10.1) | 1.36 (1.22–1.52) |
EGFR, epidermal growth factor receptor; OS, overall survival; Ref., reference.
aAdjusted for age, gender, Eastern Cooperative Oncology Group performance status, and tumor stage: Non-smokers as reference group.
bCochran-Mantel-Haenszel test for trends: Lowest level of smoking status as reference group.
The OS rate decreased significantly with an increased amount of smoking even in the EGFR-mutant patients, wherein the survival rates for those smoking for > 0–15, > 15–30, > 30–45, and > 45 pack-years were 19.5 months (95% CI, 17.8–22.4), 19.7 months (95% CI, 17.0–21.2), 17.5 months (95% CI, 15.1–19.5), and 13.5 months (95% CI, 12.0–15.4), respectively. Of note, patients who smoked < 15 pack-years had similar durations of survival as compared to non-smokers (HR, 1.10 [95% CI, 0.95–1.26], P = 0.203). In contrast, EGFR-wild type patients smoking for < 15 pack-years had a significantly worse outcome than non-smokers (HR, 1.24 [95% CI, 1.08–1.42], P = 0.002). A significant relationship was observed between an increased amount of smoking and a reduced survival duration, in both the EGFR-mutant and EGFR-wild type populations (P = 0.007 and 0.009 for trend, respectively).
With regard to the smoke-free years, we found that, among EGFR-mutant patients, current smokers had a significantly worse outcome as compared to non-smokers (HR: 1.33 [95% CI, 1.20–1.47]; P < 0.001). However, former smokers had similar survival durations as compared to non-smokers, even among those who had quit smoking for < 5 years. In contrast, among the EGFR-wild type patients, only those who had quit smoking for > 15 years had comparable survival durations as those in non-smokers.
With regard to the age of smoking initiation, EGFR-mutant patients who had only started smoking after 30 years of age had similar outcomes as non-smokers (HR, 1.03 [95% CI, 0.98–1.26], P = 0.089). However, within the EGFR-wild type group, patients who initiated smoking in all age groups had worse outcomes.
Interaction between gender and smoking status
An association has been reported between smoking behaviors and gender, particularly among Asians [17], which indicated that the smoking rate is significantly higher in men than in women. Therefore, we further analyzed the impact of gender-smoking behaviors and their interaction on the survival of patients with different EGFR mutation status.
Figure 2 outlines the Kaplan-Meier curves plotting OS with regard to gender, smoking status, and EGFR mutation status. In general, EGFR-mutant patients survived longer than EGFR-wild type patients. Among patients with the same EGFR genotypes and smoking behavior, females experienced a better outcome than males. In both EGFR-mutant and EGFR-wild type populations, female non-smokers had the best outcome, whereas male smokers had the worst outcome. Of note, female smokers had similar outcomes as male non-smokers (P = 0.901 in the EGFR-mutant group and 0.681 in the EGFR-wild type group). In the multivariate analysis, female gender was found to be an independent prognostic factor in both the EGFR-mutant and EGFR-wild type groups (HR: 0.86 [95% CI, 0.80–0.93]; P < 0.001 in the EGFR-mutant group and HR: 0.88 [95% CI, 0.81–0.96]; P = 0.004 in the EGFR-wild type group). All these observations suggest that gender may play an independent role in determining lung cancer outcome.
Figure 2: Duration of overall survival according to subgroups in terms of EGFR mutation status, smoking, and gender. Kaplan-Meier estimates of the duration of overall survival with regard to EGFR mutation status, smoking, and gender are shown. CI, confidence interval.
DISCUSSION
An increasing number of studies have been assessing the effects of smoking, particularly on the survival of lung cancer patients, and all these studies suggested that smoking is a poor prognostic factor [6, 11, 13–15]. However, most of these studies were heterogeneous with regard to tumor stage and histology, and the data were not obtained from the era of EGFR-targeted therapy. In the present study, we enrolled 11,678 Taiwanese patients with a pure adenocarcinoma histology, advanced stage disease, detailed smoking data, and known EGFR mutation status. We assessed the different aspects of smoking behaviors, and our results suggest that smoking is not only an independent predictor of a lower EGFR mutation rate, but also reduces the survival duration in both EGFR-mutant and EGFR-wild type patients.
Smoking is known as a negative predictor for the EGFR mutation. In a meta-analysis of 26 studies including 3,688 NSCLC patients, Ren et al. confirmed that non-smokers were associated with a significantly higher EGFR mutation rate [16]. Pham et al. further analyzed the influence of smoking in terms of pack- and smoke-free years on the prevalence of EGFR mutation, and found that the EGFR mutation rate was similar between non-smokers and patients who had smoked < 15 pack-years or those who had already quit smoking over the long-term [17]. In addition to smoking, both ethnicity and histology influenced the EGFR mutation rate [18]. Previous studies comprised patients with different ethnicities and histology, which may have led to different results. In the present study, we found that the EGFR mutation rate was significantly lower in smokers, even in those who had smoked for < 15 pack-years or those who had already quit smoking for > 15 years. Moreover, patients who had started smoking at a younger age also had a lower EGFR mutation rate.
The OS duration within our cohort was 16.0 months, which was longer than those of other nationwide studies [6, 11, 19]. This may be due to the inclusion of patients with pure adenocarcinoma, a greater number of non-smokers, a higher EGFR mutation rate among the Taiwanese patients, and the integration of EGFR-TKI treatment. In contrast, the OS duration of EGFR-wild type patients was 9.6 months, which was similar to the results of studies conducted prior to the EGFR-targeted therapy era. In the present study, smoking was associated with a worse OS in both EGFR-mutant and EGFR-wild type patients, and the survival duration of patients was inversely related to their levels of smoking. Moreover, we found a positive correlation between smoke-free years and outcomes, which could serve as valuable evidence for the recommendation of cigarette abstinence.
Large scale screening of oncogenic drivers of lung cancer has shown that patients with actionable genetic alterations would experience a better outcome [20, 21]. EGFR mutation is the most common oncogenic driver in Asian NSCLC patients [4, 22]. In Taiwan, the detection of EGFR mutations in advanced lung adenocarcinoma patients has become a routine procedure. Moreover, the National Health Insurance Administration has been reimbursing advanced EGFR-mutant lung adenocarcinoma patients receiving EGFR-TKI as the first-line of treatment since 2011; hence, every EGFR-mutant patient in the present study had an equal chance to receive EGFR-targeted therapy. Previous studies have identified smoking as a predictor of shorter progression-free survival among EGFR-mutant patients receiving EGFR-TKI, although its impact on OS was not consistent [23–25]. We found that smoking negatively affected OS in EGFR-mutant patients in a dose-dependent manner, despite the use of highly effective EGFR-TKI. As cigarette smoking negatively affected the outcomes to a greater extent in the EGFR-wild type population, we suggest that the lower mutation burden in EGFR-mutant tumors [26] and the high efficacy of EGFR-TKI might at least in part attenuate the negative effects of smoking among EGFR-mutant patients.
Previous studies found that DNA adduct levels were inversely associated with the age at smoking initiation among former smokers, thus indicating that young smokers are more susceptible to DNA damage and persistence of genetic alterations than those who began smoking at an older age [27]. Our study found that younger smokers had a lower EGFR mutation rate, which may be due to the dilution of the effect of more smoking-related lung cancer [28]. Furthermore, DNA damage and persistence of genetic alterations may negatively affect the survival rates of young smokers among EGFR-mutant lung cancer patients, which may consequently have substantial implications on the need for preventing adolescent smoking, particularly in this era of targeted therapy.
A relationship between gender and smoking behaviors has been observed, particularly in the Asian population [12]. Gender is known to be an important factor in determining the pathological characteristics and driver mutations of lung cancer, as female gender is associated with a greater toxicity and efficacy of treatment [29]. Our results suggest that the harboring of EGFR mutations remains the most important prognostic factor. This may be related to the high efficacy of EGFR-TKI therapy, irrespective of whether it is administered as first-line or subsequent therapies [30]. However, among the patients with the same EGFR mutation and smoking status, females usually had a better outcome than males. Of note, female non-smokers had the best outcome, which suggests that these patients would benefit more from subsequent lung cancer treatment, such as chemotherapy [29, 31]. Thus, our results imply that gender may influence the outcome of lung cancer patients through mechanisms independent of smoking.
There are 2 major limitations of the present study. First, the data were obtained from a registry database, and hence, the efficacy of a particular regimen cannot be determined. Nevertheless, we assessed OS as the primary endpoint, which is unambiguous and can be represented as a standard clinical outcome. Moreover, our patients had an equal chance for treatment owing to the fact that patients are reimbursed by the Taiwan National Health Insurance Administration for novel lung cancer therapies, such as EGFR-TKIs and pemetrexed, received over the study period. In addition, data from this period would not have been affected by the use of anaplastic lymphoma kinase (ALK) inhibitors, 3rd-generation EGFR-TKI, and immunotherapy; hence, this may accurately reflect the actual conditions in the EGFR-targeted therapy era. Second, our database did not register the detailed EGFR mutation spectrum. Based on our previous studies, primary resistant subtypes only accounted for a small portion of all EGFR mutations; [4, 32] hence, it was less likely to influence the overall results.
In conclusion, smoking reduced both the EGFR mutation rate and survival duration in advanced lung adenocarcinoma patients in a dose-dependent manner, particularly among those who started smoking at a young age. In addition to EGFR mutation and smoking, gender also played an important role in the survival of these patients. This information may be valuable when recommending cigarette abstinence. Nevertheless, the impact of gender should be further elucidated in future studies.
MATERIALS AND METHODS
Patient population
The detailed smoking history and EGFR mutation status of lung cancer patients have been routinely recorded since 2011 in the Taiwan Cancer Registry [33]. In the present study, we reviewed the information in the lung cancer database from 2011 to 2014. To be eligible for the study, patients were required to have cytologically or pathologically confirmed lung adenocarcinoma, stage IIIB or IV disease, and available follow-up survival data. Patients were excluded if they had unclear smoking or EGFR mutation information.
Clinical data for analysis included patient age, gender, histological types, tumor stage, smoking status, the Eastern Cooperative Oncology Group performance status (ECOG PS), EGFR mutation status, and overall survival (OS). Non-smokers were defined as patients who had smoked < 100 cigarettes in their lifetime, whereas others were defined as smokers. Smokers were further stratified by smoking pack-years, smoke-free years, and age of smoking initiation. Lung cancer TNM (tumor, node, and metastases) staging was conducted according to the 7th edition of American Joint Committee on Cancer (AJCC) staging system [34]. This study was approved by the Institutional Review Board of Taiwan’s National Health Research Institutes Research Ethics Committee (IRB No. CE17068B).
EGFR mutation testing
Several molecular tests are used for EGFR mutation analysis in Taiwan, including direct sequencing, protein nucleic acid-locked nucleic acid polymerase chain reaction (PNA-LNA PCR) clamp, scorpions amplification refractory mutation system (ARMS) (EGFR RGQ PCR Kit), Cobas EGFR Mutation Test, and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) [32, 35]. All are valid methods for EGFR mutation detection [36], although their use depended on the available laboratory facilities at each hospital. In Taiwan, the National Health Insurance Administration has been reimbursing patients receiving EGFR-TKI as the first-line treatment for advanced EGFR-mutant lung adenocarcinoma since 2011.
Statistical methods
Multivariate logistic regression was performed to analyze the correlation of EGFR mutation with age, gender, stage, and smoking status. For survival analysis, the survival status was evaluated according to the National Death Certificate database, maintained by the Department of Statistics, Ministry of Health and Welfare, Taiwan, and was followed up until December 31, 2015. The survival duration for each patient was defined as the time from the date of initial diagnosis to the date of death, or the date of follow-up termination. The OS was estimated using the Kaplan-Meier method, whereas the between-group differences in the OS were assessed using a stratified log-rank test. Hazard ratios (HRs) and the associated 95% confidence intervals (CIs) were estimated using the Cox proportional hazards model. The correlations between smoking intensity and EGFR mutation prevalence and survival were analyzed using the Cochran-Mantel-Haenszel test. All analyses were performed using SAS version 9.4 statistical software (SAS Institute, Cary, NC, USA).
CONFLICTS OF INTEREST
There are no conflicts of interest to declare.
FUNDING
The study was supported by a grant from the Health and Welfare Surcharge of Tobacco products provided by the Health Promotion Administration, Ministry of Health and Welfare, Taiwan (R.O.C.).
REFERENCES
1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015; 65:5–29. https://doi.org/10.3322/caac.21254.
2. Whiteman DC, Wilson LF. The fractions of cancer attributable to modifiable factors: A global review. Cancer Epidemiol. 2016; 44:203–21. https://doi.org/10.1016/j.canep.2016.06.013.
3. Wahbah M, Boroumand N, Castro C, El-Zeky F, Eltorky M. Changing trends in the distribution of the histologic types of lung cancer: a review of 4,439 cases. Ann Diagn Pathol. 2007; 11:89–96. https://doi.org/10.1016/j.anndiagpath.2006.04.006.
4. Hsu KH, Ho CC, Hsia TC, Tseng JS, Su KY, Wu MF, Chiu KL, Yang TY, Chen KC, Ooi H, Wu TC, Chen HJ, Chen HY, et al. Identification of five driver gene mutations in patients with treatment-naive lung adenocarcinoma in Taiwan. PLoS One. 2015; 10:e0120852. https://doi.org/10.1371/journal.pone.0120852.
5. Tseng JS, Wang CL, Yang TY, Chen CY, Yang CT, Chen KC, Hsu KH, Tsai CR, Chang GC. Divergent epidermal growth factor receptor mutation patterns between smokers and non-smokers with lung adenocarcinoma. Lung Cancer. 2015; 90:472–6. https://doi.org/10.1016/j.lungcan.2015.09.024.
6. Kawaguchi T, Takada M, Kubo A, Matsumura A, Fukai S, Tamura A, Saito R, Maruyama Y, Kawahara M, Ignatius Ou SH. Performance status and smoking status are independent favorable prognostic factors for survival in non-small cell lung cancer: a comprehensive analysis of 26,957 patients with NSCLC. J Thorac Oncol. 2010; 5:620–30. https://doi.org/10.1097/JTO.0b013e3181d2dcd9.
7. Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014; 511:543–50. https://doi.org/10.1038/nature13385.
8. Greenhalgh J, Dwan K, Boland A, Bates V, Vecchio F, Dundar Y, Jain P, Green JA. First-line treatment of advanced epidermal growth factor receptor (EGFR) mutation positive non-squamous non-small cell lung cancer. Cochrane Database Syst Rev. 2016; CD010383. https://doi.org/10.1002/14651858.CD010383.pub2.
9. Thongprasert S, Duffield E, Saijo N, Wu YL, Yang JC, Chu DT, Liao M, Chen YM, Kuo HP, Negoro S, Lam KC, Armour A, Magill P, et al. Health-related quality-of-life in a randomized phase III first-line study of gefitinib versus carboplatin/paclitaxel in clinically selected patients from Asia with advanced NSCLC (IPASS). J Thorac Oncol. 2011; 6:1872–80. https://doi.org/10.1097/JTO.0b013e31822adaf7.
10. Reck M, Heigener DF, Mok T, Soria JC, Rabe KF. Management of non-small-cell lung cancer: recent developments. Lancet. 2013; 382:709–19. https://doi.org/10.1016/S0140-6736(13)61502-0.
11. Ferketich AK, Niland JC, Mamet R, Zornosa C, D'Amico TA, Ettinger DS, Kalemkerian GP, Pisters KM, Reid ME, Otterson GA. Smoking status and survival in the national comprehensive cancer network non-small cell lung cancer cohort. Cancer. 2013; 119:847–53. https://doi.org/10.1002/cncr.27824.
12. Tsai YW, Tsai TI, Yang CL, Kuo KN. Gender differences in smoking behaviors in an Asian population. J Womens Health (Larchmt). 2008; 17:971–8. https://doi.org/10.1089/jwh.2007.0621.
13. Flanders WD, Lally CA, Zhu BP, Henley SJ, Thun MJ. Lung cancer mortality in relation to age, duration of smoking, and daily cigarette consumption: results from Cancer Prevention Study II. Cancer Res. 2003; 63:6556–62.
14. Parsons A, Daley A, Begh R, Aveyard P. Influence of smoking cessation after diagnosis of early stage lung cancer on prognosis: systematic review of observational studies with meta-analysis. BMJ. 2010; 340:b5569. https://doi.org/10.1136/bmj.b5569.
15. Tammemagi CM, Neslund-Dudas C, Simoff M, Kvale P. Smoking and lung cancer survival: the role of comorbidity and treatment. Chest. 2004; 125:27–37.
16. Ren JH, He WS, Yan GL, Jin M, Yang KY, Wu G. EGFR mutations in non-small-cell lung cancer among smokers and non-smokers: a meta-analysis. Environ Mol Mutagen. 2012; 53:78–82. https://doi.org/10.1002/em.20680.
17. Pham D, Kris MG, Riely GJ, Sarkaria IS, McDonough T, Chuai S, Venkatraman ES, Miller VA, Ladanyi M, Pao W, Wilson RK, Singh B, Rusch VW. Use of cigarette-smoking history to estimate the likelihood of mutations in epidermal growth factor receptor gene exons 19 and 21 in lung adenocarcinomas. J Clin Oncol. 2006; 24:1700–4. https://doi.org/10.1200/JCO.2005.04.3224.
18. Shigematsu H, Lin L, Takahashi T, Nomura M, Suzuki M, Wistuba II, Fong KM, Lee H, Toyooka S, Shimizu N, Fujisawa T, Feng Z, Roth JA, et al. Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst. 2005; 97:339–46. https://doi.org/10.1093/jnci/dji055.
19. Jakobsen E, Rasmussen TR, Green A. Mortality and survival of lung cancer in Denmark: Results from the Danish Lung Cancer Group 2000–2012. Acta Oncol. 2016; 55:2–9. https://doi.org/10.3109/0284186X.2016.1150608.
20. Barlesi F, Mazieres J, Merlio JP, Debieuvre D, Mosser J, Lena H, Ouafik L, Besse B, Rouquette I, Westeel V, Escande F, Monnet I, Lemoine A, et al. Routine molecular profiling of patients with advanced non-small-cell lung cancer: results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT). Lancet. 2016; 387:1415–6. https://doi.org/10.1016/S0140-6736(16)00004-0.
21. Kris MG, Johnson BE, Berry LD, Kwiatkowski DJ, Iafrate AJ, Wistuba II, Varella-Garcia M, Franklin WA, Aronson SL, Su PF, Shyr Y, Camidge DR, Sequist LV, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA. 2014; 311:1998–2006. https://doi.org/10.1001/jama.2014.3741.
22. Shi Y, Au JS, Thongprasert S, Srinivasan S, Tsai CM, Khoa MT, Heeroma K, Itoh Y, Cornelio G, Yang PC. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol. 2014; 9:154–62. https://doi.org/10.1097/JTO.0000000000000033.
23. Hasegawa Y, Ando M, Maemondo M, Yamamoto S, Isa S, Saka H, Kubo A, Kawaguchi T, Takada M, Rosell R, Kurata T, Ou SH. The role of smoking status on the progression-free survival of non-small cell lung cancer patients harboring activating epidermal growth factor receptor (EGFR) mutations receiving first-line EGFR tyrosine kinase inhibitor versus platinum doublet chemotherapy: a meta-analysis of prospective randomized trials. Oncologist. 2015; 20:307–15. https://doi.org/10.1634/theoncologist.2014–0285.
24. Sohn HS, Kwon JW, Shin S, Kim HS, Kim H. Effect of smoking status on progression-free and overall survival in non-small cell lung cancer patients receiving erlotinib or gefitinib: a meta-analysis. J Clin Pharm Ther. 2015; 40:661–71. https://doi.org/10.1111/jcpt.12332.
25. Zhang Y, Kang S, Fang W, Hong S, Liang W, Yan Y, Qin T, Tang Y, Sheng J, Zhang L. Impact of smoking status on EGFR-TKI efficacy for advanced non-small-cell lung cancer in EGFR mutants: a meta-analysis. Clin Lung Cancer. 2015; 16:144–51.e1. https://doi.org/10.1016/j.cllc.2014.09.008.
26. McFadden DG, Politi K, Bhutkar A, Chen FK, Song X, Pirun M, Santiago PM, Kim-Kiselak C, Platt JT, Lee E, Hodges E, Rosebrock AP, Bronson RT, et al. Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma. Proc Natl Acad Sci U S A. 2016; 113:E6409-E17. https://doi.org/10.1073/pnas.1613601113.
27. Wiencke JK, Thurston SW, Kelsey KT, Varkonyi A, Wain JC, Mark EJ, Christiani DC. Early age at smoking initiation and tobacco carcinogen DNA damage in the lung. J Natl Cancer Inst. 1999; 91:614–9.
28. Mitsudomi T. Molecular epidemiology of lung cancer and geographic variations with special reference to EGFR mutations. Transl Lung Cancer Res. 2014; 3:205–11. https://doi.org/10.3978/j.issn.2218-6751.2014.08.04.
29. Isla D, Majem M, Vinolas N, Artal A, Blasco A, Felip E, Garrido P, Remon J, Baquedano M, Borras JM, Die Trill M, Garcia-Campelo R, Juan O, et al. A consensus statement on the gender perspective in lung cancer. Clin Transl Oncol. 2016. https://doi.org/10.1007/s12094-016-1578-x.
30. Lee CK, Brown C, Gralla RJ, Hirsh V, Thongprasert S, Tsai CM, Tan EH, Ho JC, Chu da T, Zaatar A, Osorio Sanchez JA, Vu VV, Au JS, et al. Impact of EGFR inhibitor in non-small cell lung cancer on progression-free and overall survival: a meta-analysis. J Natl Cancer Inst. 2013; 105:595–605. https://doi.org/10.1093/jnci/djt072.
31. Cataldo JK, Dubey S, Prochaska JJ. Smoking cessation: an integral part of lung cancer treatment. Oncology. 2010; 78:289–301. https://doi.org/10.1159/000319937.
32. Tseng JS, Wang CL, Huang MS, Chen CY, Chang CY, Yang TY, Tsai CR, Chen KC, Hsu KH, Tsai MH, Yu SL, Su KY, Wu CW, et al. Impact of EGFR mutation detection methods on the efficacy of erlotinib in patients with advanced EGFR-wild type lung adenocarcinoma. PLoS One. 2014; 9:e107160. https://doi.org/10.1371/journal.pone.0107160.
33. Chiang CJ, Chen YC, Chen CJ, You SL, Lai MS, Taiwan Cancer Registry Task Force. Cancer trends in Taiwan. Jpn J Clin Oncol. 2010; 40:897–904. https://doi.org/10.1093/jjco/hyq057.
34. Bakker EC, van Houwelingen AC, Hornstra G. Early nutrition, essential fatty acid status and visual acuity of term infants at 7 months of age. Eur J Clin Nutr. 1999; 53:872–9.
35. Kimura H, Ohira T, Uchida O, Matsubayashi J, Shimizu S, Nagao T, Ikeda N, Nishio K. Analytical performance of the cobas EGFR mutation assay for Japanese non-small-cell lung cancer. Lung Cancer. 2014; 83:329–33. https://doi.org/10.1016/j.lungcan.2013.12.012.
36. Lindeman NI, Cagle PT, Beasley MB, Chitale DA, Dacic S, Giaccone G, Jenkins RB, Kwiatkowski DJ, Saldivar JS, Squire J, Thunnissen E, Ladanyi M. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J Thorac Oncol. 2013; 8:823–59. https://doi.org/10.1097/JTO.0b013e318290868f.