Skip to main content
Chinese Medical Journal logoLink to Chinese Medical Journal
. 2023 Jun 30;136(16):1937–1948. doi: 10.1097/CM9.0000000000002729

Persistent increase and improved survival of stage I lung cancer based on a large-scale real-world sample of 26,226 cases

Chengdi Wang 1, Jun Shao 1, Lujia Song 1, Pengwei Ren 1, Dan Liu 1, Weimin Li 1,
Editors: Ting Gao1, Xiuyuan Hao1
PMCID: PMC10431578  PMID: 37394562

Abstract

Background:

Lung cancer prevails and induces high mortality around the world. This study provided real-world information on the evolution of clinicopathological profiles and survival outcomes of lung cancer, and provided survival information within stage I subtypes.

Methods:

Patients pathologically confirmed with lung cancer between January 2009 and December 2018 were identified with complete clinicopathological information, molecular testing results, and follow-up data. Shifts in clinical characteristics were evaluated using χ 2 tests. Overall survival (OS) was calculated through the Kaplan–Meier method.

Results:

A total of 26,226 eligible lung cancer patients were included, among whom 62.55% were male and 52.89% were smokers. Non-smokers and elderly patients took increasingly larger proportions in the whole patient population. The proportion of adenocarcinoma increased from 51.63% to 71.80%, while that of squamous carcinoma decreased from 28.43% to 17.60%. Gene mutations including EGFR (52.14%), KRAS (12.14%), and ALK (8.12%) were observed. Female, younger, non-smoking, adenocarcinoma patients and those with mutated EGFR had better survival prognoses. Importantly, this study validated that early detection of early-stage lung cancer patients had contributed to pronounced survival benefits during the decade. Patients with stage I lung cancer, accounted for an increasingly considerable proportion, increasing from 15.28% to 40.25%, coinciding with the surgery rate increasing from 38.14% to 54.25%. Overall, period survival analyses found that 42.69% of patients survived 5 years, and stage I patients had a 5-year OS of 84.20%. Compared with that in 2009–2013, the prognosis of stage I patients in 2014–2018 was dramatically better, with 5-year OS increasing from 73.26% to 87.68%. Regarding the specific survival benefits among stage I patients, the 5-year survival rates were 95.28%, 93.25%, 82.08%, and 74.50% for stage IA1, IA2, IA3, and IB, respectively, far more promising than previous reports.

Conclusions:

Crucial clinical and pathological changes have been observed in the past decade. Notably, the increased incidence of stage I lung cancer coincided with an improved prognosis, indicating actual benefits of early detection and management of lung cancer.

Keywords: Lung neoplasms, Clinicopathological characteristics, TNM staging, Pathological subtypes, Survival analysis

Introduction

Lung cancer still imposes an enormous burden around the world leading to the majority of malignancy-related deaths.[1] In China, where the lung cancer population contributed to a considerable part of new cases and death cases among all countries,[2,3] despite the substantial technical developments in lung cancer diagnosis and treatment, the 5-year overall survival (OS) rate of lung cancer in the Chinese population was poor.[4,5] The dismal prognosis may be partially explained by the high proportion of lung cancer patients diagnosed at an advanced stage. For better lung cancer management and mortality reduction, computed tomography (CT) is recommended for lung cancer screening.[6,7]

A wide variation in lung cancer incidence and survival rates exists across a wide range of clinical traits.[8] Sex and age are both important clinical characteristics among lung cancer patients. Over the past few decades in the United States, the proportions of female lung cancer patients have dramatically increased among the whole patient population, especially the younger age-specific group.[9] The stage at diagnosis is crucial for choosing the treatment strategies and hinting at possible prognoses of patients with lung cancer. Compared with patients with advanced cancer, those diagnosed with early-stage disease are more likely to undergo curative surgical resection and have a better outcome.[10] The dynamics of sociodemographic characteristics and clinicopathologic features have been evolving, which would be fundamental for both decisions regarding medical intervention and the prediction of patient prognosis.

Meanwhile, given that lung cancer is also highly heterogenous and complicated on molecular level,[11] investigations into multiple recurrent alternations within the large patient group could contribute to the discovery of clinically actionable drug targets. Mutant epidermal growth factor receptor (EGFR) is one of the most prevalently activated oncogenes in both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC),[12,13] and abnormalities in V-Raf murine sarcoma viral oncogene homolog B1 (BRAF) and erb-b2 receptor tyrosine kinase 2 (ERBB2) have emerged in the expanding category of approved targets for treatment.[14,15] Additionally, mutations affecting tumor suppressor genes such as tumor protein p53 (TP53) are also increasingly concerned.[16] Given the genomic landscape of lung cancer is extremely complicated, a better understanding of the composition of the mutational profile would be needed to make an informed clinical decision.

Lung cancer characteristics in the real world are extremely region-specific. China had a high prevalence of tobacco use, accounting for the majority of smokers of the world.[17] And the genomic traits vary in different ethnicities, exemplified by EGFR mutations harboring a frequency of over 50% in the Asian population, but less prevalent in western countries.[18,19] We noted that there still lacks a thorough dissection into the lung cancer features in China based on a large actual population. Additionally, little is known about the clinical and genomic characteristics and how they have evolved in this country in the past few years.

Therefore, here, we aimed to examine the current status and changes in lung cancer clinicopathological characteristics, mutation profiles, and outcomes during the decade based on real-world large-scale samples. Furthermore, the changing trends of stage I lung cancer incidence and survival prognosis were also investigated.

Methods

Data source

The data of this retrospective study were obtained from the Lung Cancer Database of West China Hospital, Sichuan University and its integrated care organizations, which was a lung cancer-specific database integrating electronic medical records, demographic information, and follow-up data. This database had been established based on the medical record system of the grade-A tertiary hospital. All detailed information should be abstracted manually by at least two specialized staffs independently or be exported in batches and then carefully checked. Every inconsistency would be resolved with rigorous reviews by senior clinical experts to enhance the good accuracy of data. All patients included provided written informed consent in advance, and this study had undergone a rigorous review process by the esteemed Ethics Committee of West China Hospital, Sichuan University (No. 2020 [232]).

Sampling and quality control

We had a thorough overview of the whole electronic database. All eligible cases with pathologically confirmed primary lung cancer who were diagnosed in West China Hospital, Sichuan University between January 2009 and December 2018 were collected. Patients with complete clinical/genomic characteristics were included. The pathological results were obtained through surgery, fiberoptic bronchoscopy, percutaneous lung puncture, pleural effusion, lymph node biopsy, sputum cytology, etc. We collected the following data from patients: sex, age at diagnosis, smoking history, family history of lung cancer, pathological types, pathological subtypes, clinical or pathological staging, and genomic characteristics. Follow-up was conducted for all patients until the end of September 2022 or till their death. To affirm privacy, sensitive information such as family address and citizen identity document (ID) were hidden; and other complete clinical traits were extracted from the Lung Cancer Database. In the extracted data, we double-checked the completeness and accuracy of information for all patients. Patients who were only clinically diagnosed, had lung metastasis from extrapulmonary cancers,with key information missing, or not properly followed up should be excluded. Data quality control procedures were conducted at several rounds. Reasons for exclusion would be carefully indicated in our final documents used for analyses.

Clinical characteristics

Regarding age, patients were subclustered into three groups: young (<45 years old), middle (45–59 years old), and elderly (≥60 years old). Ever-smoking patients included current or former smokers. According to the classification standards of lung tumors issued by the World Health Organization in 2015,[20] primary lung cancer cases could be divided into LUAD, LUSC, small cell lung cancer (SCLC), and others. Tumors with multiple components were classified according to the pathological results of the main components. Tumor staging was carried out according to the tumor-node-metastasis (TNM) staging system.[21] If data on the pathological stage were missing, clinical stage data were used instead. Treatment strategies involved surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy. The main endpoint in our study was OS, measured from the date of lung cancer diagnosis to death. If the accurate date of death was lost, the date of the patient's last follow-up was considered in later analyses.

Genomic detection

Among the established tumor driver genes,[22] our study considered information on EGFR,Kirsten rat sarcoma viral oncogene homologue (KRAS), mesenchymal-epithelial transition factor (MET), anaplastic lymphoma receptor tyrosine kinase (ALK), ERBB2, BRAF, ROS proto-oncogene 1 (ROS1), and rearranged during transfection (RET) mutation status. In routine clinical practice for lung cancer patients, molecular testing was fundamentally based on guideline recommended testing methods like immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), or next-generation sequencing (NGS).[23] Biomarkers found in genomic detection indicated the responses to subsequent targeted and immune-oncology agents. In our study, these details were retrospectively summarized alongside with the clinicopathological characteristics.

Data processing and statistical analyses

All statistical analyses were performed based on IBM SPSS Statistics for Windows, Version 23.0. (IBM Corp. Armonk, NY, USA) and R Statistical Software (Version 4.1.0, https://www.r-project.org/). The quantitative information was presented with the number of cases and the percentages, while the qualitative information was presented with the mean, standard deviation, and 95% confidence interval (CI). The χ2 test, Kruskal–Wallis H rank test, and Spearman rank correlation test were used in our study. OS was evaluated through Kaplan–Meier plots and log-rank tests. A two-tailed P value less than 0.05 was considered significant.

Results

General outline of a large-scale database with 26,226 registered lung cancer patients

A total of 26,226 patients pathologically diagnosed with lung cancer from 2009 to 2018 were eligibly enrolled. As illustrated in Table 1, a total of 16,404 (62.55%) participants were male and 13,871 (52.89%) participants were ever smokers. The young group (<45 years old), middle-aged group (45–59 years old), and elderly group (≥60 years old) accounted for 9.98% (2618/26,226), 38.75% (10,163/26,226), and 51.27% (13,445/26,226), respectively. The vast majority of people had no family history of lung cancer (n = 24,806, 94.59%). LUAD was the most frequently occult pathological subtype, with 16,371 cases accounting for 62.42% of the entire patient population, followed by LUSC with 6033 (23.00%) cases, and SCLC with 2202 (8.40%) cases. Stage IV disease was the predominant diagnosed stage, with 10,640 patients accounting for 40.57% of the entire patient population. Stage I, stage II, and stage III accounted for approximately 25.97% (6811/26,226), 9.23% (2421/26,226), and 23.90% (6268/26,226) of the entire patient population, respectively. Possibly due to the relatively advanced disease stage at diagnosis, fewer than half of the patients underwent surgery (11,970/26,226, 45.64%), which usually had a possibility of curative intent.

Table 1.

Clinicopathological characteristics of 26,226 lung cancer patients.

Characteristics Total (N = 26,226) 2009–2013 (N = 9134) 2014–2018 (N = 17,092) Statistics (χ2) P values
Sex 130.02 <0.001
Male 16,404 (62.55) 6139 (67.21) 10,265 (60.06)
Female 9822 (37.45) 2995 (32.79) 6827 (39.94)
Age at diagnosis 28.41 <0.001
<45 years 2618 (9.98) 1012 (11.08) 1606 (9.40)
45–59 years 10,163 (38.75) 3609 (39.51) 6554 (38.35)
≥60 years 13,445 (51.27) 4513 (49.41) 8932 (52.26)
Smoking history 140.81 <0.001
Never 12,206 (46.54) 3800 (41.61) 8406 (49.18)
Ever 13,871 (52.89) 5288 (57.89) 8583 (50.22)
Unknown 149 (0.57) 46 (0.50) 103 (0.60)
Family history of lung cancer 18.98 <0.001
Yes 1420 (5.41) 418 (4.58) 1002 (5.86)
No 24,806 (94.59) 8716 (95.42) 16,090 (94.14)
Pathologic subtypes 402.25 <0.001
LUAD 16,371 (62.42) 4960 (54.30) 11,411 (66.76)
LUSC 6033 (23.00) 2516 (27.55) 3517 (20.58)
SCLC 2202 (8.40) 989 (10.83) 1213 (7.10)
Others 1620 (6.18) 669 (7.33) 951 (5.56)
Stage 643.07 <0.001
I* 6811 (25.97) 1511 (16.54) 5300 (31.01)
IA 4303 (16.41) 608 (6.66) 3695 (21.62)
IA1 1227 (4.68) 85 (0.93) 1142 (6.68)
IA2 1909 (7.28) 248 (2.72) 1661 (9.72)
IA3 1167 (4.45) 275 (3.01) 892 (5.22)
IB 2361 (9.00) 835 (9.14) 1526 (8.93)
II 2421 (9.23) 983 (10.76) 1438 (8.41)
III 6268 (23.90) 2432 (26.63) 3836 (22.44)
IV 10,640 (40.57) 4155 (45.48) 6485 (37.95)
Unknown 86 (0.33) 53 (0.58) 33 (0.19)
Surgery 287.32 <0.001
Yes 11,970 (45.64) 3517 (38.50) 8453 (49.46)
No 14,256 (54.36) 5617 (61.50) 8639 (50.54)

Data are presented as n (%). LUAD: Lung adenocarcinoma; LUSC: Lung squamous carcinoma; SCLC: Small cell lung cancer. *Detailed staging information was unavailable for 147 patients with stage I lung cancer; Stage was define based on TNM stage groups.

Ten-year evolution of clinicopathological characteristics

During the decade from 2009 to 2018, there were varying degrees of changes in the clinicopathological characteristics of lung cancer patients in terms of sex, smoking history, pathologic subtype, cancer stage, treatment strategy, and age [Figure 1].

Figure 1.

Figure 1

Evolutions in clinicopathologic characteristics of lung cancer patients from 2009 to 2018: (A) sex; (B) smoking history; (C) histology; (D) stage; (E) surgery; and (F) age. LUAD: Lung adenocarcinoma; LUSC: Lung suamous cell carcinoma; SCLC: Small cell lung cancer.

The ratio of males to females changed from 2.34:1.00 to 1.33:1.00, and the gap between male and female proportions gradually narrowed. The percentage of male patients decreased from 70.05% (966/1379) to 57.04% (2308/4046), and simultaneously, the percentage of females increased from 29.95% (413/1379) to 42.96% (1738/4046) [Figure 1A]. Notably, there was a remarkable increase of non-smokers in the patient group. The smoking proportion of lung cancer patients decreased from 58.52% (807/1379) to 47.26% (1912/4046) [Figure 1B]. Considering there was a sex difference in terms of smoking popularity, the increase in female lung cancer cases might explain the growing number of non-smoking patients. Additionally, it was believed that the incidence of lung cancer in women was highly confined to LUAD,[9] and the variations in the pathological subtype distributions could also be confounded by sex. During the decade, the proportion of LUAD increased each year, from 51.63% (712/1379) in 2009 to 71.80% (2905/4046) in 2018, while the proportion of LUSC decreased, from 28.43% (392/1379) in 2009 to 17.60% (712/4046) in 2018 [Figure 1C]. The proportion of SCLC displayed a gradual declining trend during ten years, in spite of a few minor fluctuations.

Before 2013, the percentages of each stage fluctuated but remained relatively steady, after which there was a major increased trend in stage I lung cancer cases, alongside a decreased trend in other three stages. In 2017, when the proportion of stage I patients exceeded that of stage IV patients. In 2009, stage IV disease was the predominant stage diagnosed and decreased from 48.98% (670/1368) to 34.07% (1377/4042) in 2018 [Figure 1D]. Stage I cases initially accounted for only 15.28% (209/1368) in 2009 and finally rose to 40.25% (1627/4042) in 2018 among the general patient population [Figure 1D], which might also contribute to the climbing rates of surgery among lung cancer patients [Figure 1E]. Moreover, the proportion of patients in the young group, middle-aged group, and elderly group varied slightly from 13.05% (180/1379), 37.49% (517/1379), and 49.46% (682/1379) to 9.57% (387/4046), 39.55% (1600/4046), and 50.89% (2059/4046), respectively [Figure 1F]. The distribution of age groups was relatively steady compared with other radically evolving characteristics.

Prognostic signals among clinicopathological characteristics

We collected follow-up information on the survival outcomes of enrolled patients until the September of 2022. Estimates of survival were summarized in Figure 2. Overall, the 1-year survival for registered lung cancer patients was approximately 73.68% and the 5-year survival was 42.69% [Table 2, Figure 2A]. Sex, diagnosis age, smoking history, histology, stage, surgery and diagnosis year (before/after 2013) were all significantly associated with survival outcomes (P <0.001) [Figures 2B–H].

Figure 2.

Figure 2

Overall survival curves by clinicopathologic characteristics: (A) all patients; (B) sex; (C) age; (D) smoking history; (E) histology; (F) stage; (G)surgery; and (H) diagnosis year. CI: Confidence interval; LUAD: Lung adenocarcinoma; LUSC: Lung suamous cell carcinoma; NA: Not applicable; SCLC: Small cell lung cancer. Dashed lines represent the median survival time.

Table 2.

Survival analyses among lung cancer patients with different characteristics.

Characteristics Period survival rate (%) Median OS (95% CI) (months) P values
1-year 2-year 3-year 4-year 5-year
Overall 73.68 58.54 50.74 46.12 42.69 38 (37–39)
Diagnosis year <0.001
2009–2013 72.67 56.37 47.60 41.63 37.64 33 (31–34)
2014–2018 74.21 59.70 52.43 48.57 45.67 43 (41–46)
Sex <0.001
Male 69.33 52.53 44.68 40.31 37.20 27 (26–29)
Female 80.93 68.58 60.87 55.84 51.87 67 (64–72)
Age
<45 years 77.77 63.37 55.42 50.97 48.05 52 (46–61)
45–59 years 77.42 62.25 54.90 50.46 47.08 50 (47–54)
≥60 years 70.05 54.80 46.69 41.90 38.35 31 (30–32)
Smoking history <0.001
Never 80.71 68.05 60.12 55.15 51.11 65 (61–69)
Ever 67.46 50.15 42.48 38.20 35.30 25 (24–26)
Histology <0.001
LUAD 78.12 65.23 57.28 52.36 48.48 55 (53–58)
LUSC 69.28 50.32 42.24 37.92 35.16 25 (24–26)
SCLC 58.67 36.83 29.79 26.28 24.28 16 (15–17)
Others 65.56 51.54 44.88 40.71 37.32 26 (23–31)
Stage <0.001
I 95.99 92.29 89.24 86.97 84.20 NA
IA1 98.86 97.64 97.15 96.73 95.28 NA
IA2 98.90 97.49 96.12 95.04 93.25 NA
IA3 96.40 90.92 87.23 84.25 82.08 NA
IB 92.84 87.55 82.38 78.58 74.50 NA
II 86.74 73.88 66.12 60.62 56.41 83 (77–93)
III 72.21 52.57 43.25 37.83 34.39 27 (26–29)
IV 57.33 37.05 27.07 21.70 18.41 16 (15–16)
Surgery <0.001
Yes 92.66 84.87 79.08 74.88 71.16 NA
No 57.74 36.44 26.95 22.00 18.95 16 (16–16)

CI: Confidence interval; HR: Hazard ratio; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; NA: Not applicable; OS: Overall survival; SCLC: Small cell lung cancer.

Period survival estimates were lower for men than women (5-year estimate: 37.20% vs. 51.87%) [Figure 2B] and worse for elderly patients than middle-aged and young patients (5-year estimate: 38.35% vs. 47.08% vs. 48.05%) [Figure 2C]. Non-smokers had a better 5-year survival rate than ever-smokers (51.11% vs. 35.30%) [Figure 2D]. Additionally, LUAD, the histological subtype dominant in women, was evaluated to have a significantly better prognosis (5-year rate: 48.48% compared with 35.16% for LUSC, 24.28% for SCLC, and 37.32% for others) [Figure 2E]. In our patients, the SCLC subpopulation, whose survival outcomes were believed to be exceptionally poor,[24] indeed showed the worst prognosis. Additionally, the outcomes of LUSC and other subtypes were in the middle of LUAD and SCLC. Although LUAD currently had the most frequent incidence, the total amount of other subtypes was still considerable.

Regarding staging, the entire cohort was scattered in 10 years, a long-time range during which the standardized staging strategy has been changed. Given this, before we initiated the current analyses, we checked each patient's tumor stage according to the 8th edition of the TNM staging system. According to our results, the contemporary staging strategy had demonstrated a fancy ability to stratify patients with different levels of risk. Differences in prognoses among adjacent stage groups were statistically significant (P <0.001). The 5-year survival rates of stage I, II, III, and IV lung cancer were 84.20%, 56.41%, 34.39%, and 18.41%, respectively (P <0.001) [Figure 2F]. The curative intent surgery was also proven to bring actual benefits to prognosis, with 71.16% of those who had undergone surgery surviving over 5 years [Figure 2G], coinciding with the superior survival of stage I. Besides, there were also divergent survival outcomes before and after the year 2013, when the screening was officially proposed. The much average survival increased to 45.67% compared with 37.64% with diagnosis year 2013 as the separate point [Figure 2H]. This finding suggested the actual survival benefits of early detection and in-time management of lung cancer, which came along with the recommendation of CT screening.

Increased detection rates and improved prognosis of stage I lung cancers

We found a shift in the clinical stages among the lung cancer population during the 10 years. Initially, most lung cancers were diagnosed at stage IV. As time went by, the percentage of stage I patients in all newly diagnosed cases increased and finally became the predominant diagnosis constituting 40.25% in 2018, while the percentage of stage IV experienced a gradual decline [Figure 1D]. Furthermore, survival analyses revealed a promising survival outcome for stage I lung cancer patients. Encouragingly, stage I patients exhibited a 5-year OS of 84.20%, and had experienced a significant survival increase during the decade. [Table 2, Supplementary Table 1, http://links.lww.com/CM9/B657].

Stage I patients could further be divided into IA and IB, and IA patients could subsequently be subclassified into IA1, IA2, and IA3. Initially, in 2009, the detection of early-stage lung cancer was limited: stage I lung cancer patients only took a 15.28% (209/1368) among all cases in 2009 [Figure 1D]. The inflection point arrived in 2013 after the recommendation of CT screening. In 2018, the proportions of each stage I subtype in the annual newly diagnosed cases increased, especially those for the two earliest stages (IA1 and IA2), experiencing an elevation from 0.80% (11/1368) to 10.48% (424/4042) and from 1.46% (20/1368) to 14.13% (571/4042), respectively [Figure 3A]. And early detection, along with proper in-time management, has demonstrated pronounced survival benefits. In our study, the earliest stage IA1 had the best 5-year survival rates of 95.28% [Table 2, Figure 3B].Over the past decade, there had been a striking increase from 73.26% (2009-2013) to 87.68% (2014-2018) of the 5-year OS for stage I lung cancer patients, and the survival rates for finer stage I patients had also demonstrated noteworthy increases [Supplementary Table 1, http://links.lww.com/CM9/B657]

Figure 3.

Figure 3

Insights into finer stage I lung cancer subtypes including IA1, IA2, IA3, and IB (A) incidence of finer stage I subtypes among whole patient population; (B) overall survival curves of finer stage I subtypes.

Therefore, in the actual Chinese population specifically, there have been explicitly increased early diagnosis and promising survival benefits over the decade in lung cancer patients.

Deep insights into lung cancer genomics and relative prognostic implications

Figure 4 presented the genomic characterization of 1540 lung cancer patients whose tumor tissues had undergone molecular testing, illustrating the frequency of driver mutations in critical genes. Generally, EGFR mutations and wild-type status showed an even distribution among all patients. However, there existed a significant difference between subtypes: more than half (751/1266) LUAD patients carried EGFR mutations, while a majority of 82.46% (141/171) LUSC patients were identified as EGFR-wild-type. KRAS was prevalent in approximately 12.14% (187/1540) of all populations and 12.56% (159/1266) in LUAD. The exact distribution of genomic characteristics among lung cancer patients was shown in Supplementary Table 2, http://links.lww.com/CM9/B657. The results confirmed that EGFR was the most frequently mutated driver gene in Chinese lung cancer patients. Classic EGFR mutations include deletions in EGFR exon 19 and mutations in exon21,[25] which have significant relevance for targeted therapies and immunotherapies. In addition, more than 90% of patients did not harbor MET, ALK, ERBB2, BRAF, ROS1, and RET mutation, which was universal in both the LUAD and LUSC cohorts [Figure 4].

Figure 4.

Figure 4

Prevalence of driver mutations in critical genes for patients with lung cancer in adenocarcinoma and squamous carcinoma. Positive stands for harboring mutation, while negative stands for being wild-type. LUAD: Lung adenocarcinoma; LUSC: Lung suamous cell carcinoma; EGFR: Epidermal growth factor receptor; KRAS: Kirsten rat sarcoma viral oncogene homologue; MET: Mesenchymal-epithelial transition factor; ALK: Anaplastic lymphoma receptor tyrosine kinase; ERBB2: Erb-b2 receptor tyrosine kinase 2; BRAF: V-Raf murine sarcoma viral oncogene homolog B1; ROS1: ROS proto-oncogene 1; RET: Rearranged during transfection.

We also attempted to describe the associations between driver mutations and clinical outcomes. The following results could be consulted in Figure 5. Among all the genomic characteristics we profiled, EGFR, KRAS, and MET showed a statistically significant impact on OS regarding their mutation statuses, with P values less than 0.001 [Figure 5A–C]. EGFR-mutated patients demonstrated better survival than wild-type patients, while KRAS and MET mutations both had the reverse effect [Figure 5A–C]. Surprisingly, despite our large sample size, genes including ALK, ERBB2, BRAF, ROS1, and RET did not exhibit a significant prognostic impact, with P values of 0.319, 0.808, 0.608, 0.260, and 0.240, respectively [Figures 5D–H].

Figure 5.

Figure 5

Overall survival curves by genomic mutations: (A) EGFR; (B) KRAS (C) MET; (D) ALK; (E) ERBB2; (F) BRAF; (G) ROS1; and (H) RET. Positive stands for harboring mutation, while negative stands for being wild-type. Dashed lines represent the median survival time. EGFR: Epidermal growth factor receptor; KRAS: Kirsten rat sarcoma viral oncogene homologue; MET : Mesenchymal-epithelial transition factor; ALK: Anaplastic lymphoma receptor tyrosine kinase; ERBB2: Erb-b2 receptor tyrosine kinase 2; BRAF : V-Raf murine sarcoma viral oncogene homolog B1; ROS1: ROS proto-oncogene 1; RET: Rearranged during transfection.

Discussion

Guided by the primary focus of this study to present the most recent lung cancer statistics in the actual Chinese population, we included 26,226 patients diagnosed from January 2009 to December 2018 in West China Hospital, Sichuan University with pathologically confirmed lung cancer and comprehensively characterized demographic, pathological, and genomic features. Furthermore, we targeted the potential prognostic factors through survival analyses. Our study has provided a valuable reference for real-world lung cancer epidemiological study with multidimensional features on a relatively large scale.

A stage shift toward early-stage lung cancer, especially stages IA1 and IA2, was observed in our cohort. Indeed, the recommendation of chest CT screening among the Chinese public has brought about a tipping point in the detection of early-stage lung cancer cases,[26] and our results further reinforced the actual survival benefits of this generalization. As early as 2011, the randomized controlled trial, National Lung Screening Trial (NLST), supported the necessity of CT screening in reducing lung cancer mortality.[6] Then, in 2013, the United States Preventive Services Task Force (USPSTF) officially recommended CT screening for potential lung cancer patients.[27] This attempt has obviously contributed to an increased detection rate as well as improved survival outcomes.[28] Our study contained a relatively large sample size among the non-white population to date, adding to the real-world evidence of CT screening application in high-risk populations of lung cancer.

In our study, there was a downward trend in patients with lung cancer with a history of smoking, while the number of non-smoking lung cancer patients has been on the rise. Smoking is one of the leading risk factors inducing human disease and mortality;[29] it is associated with 80% of lung cancer cases as well as other 11 types of cancer.[30] Globally, the smoking rate is decreasing, thereby improving survival rates. In the United States, the mortality rate of lung cancer decreased by 31% in 2018 compared with the peak value in 1991 which can be partially attributed to the steady reduction in the smoking rate.[1] Consistent with our results, in recent years, smoking has tended to be less prevalent in the Chinese population,[31] possibly due to strict smoking cessation and increased awareness of health. In addition, notably, even for current early-stage lung cancer patients, smoking cessation has been proven to materially improve their outcomes.[32]

Our reported trends of the changes in the clinicopathological traits from the large-scale database are a mirror reflecting the epidemiologic evolution of lung cancer during the 10 years. This study has provided crucial information on the detailed lung cancer survival outcomes by stage and especially finer stage I classifications (IA1, IA2, IA3, and IB) in a real-world Chinese population. For our whole patient cohort, the 5-year survival rate was 42.69%, far better than previously reported survival rates.[5,33] Notably, we observe that after 2013, the detection of early-stage lung cancer patients, especially stage I patients, has been dramatically increased. Among all stage I patients, 84.20% survived after 5 years, among which stage IA1 patients had the best 5-year survival rate of 95.28%, followed by stage IA2, IA3, and IB patients at 93.25%, 82.08%, and 74.50%, respectively. A previous study of 16 countries reported early-stage lung cancer-weighted survival and demonstrated a 5-year survival rate of 92% for clinical stage IA1 patients, 83% for stage IA2 patients, 77% for stage IA3 patients, and 68% for stage IB patients.[21] Regarding specific studies in certain countries, the 5-year survival was 68.4% for stage I patients and 26.4% for overall NSCLC patients in the American population.[33] Due to limited medical resources in southwestern China, achieving such promising survival outcomes comparable to developed regions has been especially encouraging

The 5-year survival exceedingly promoted for overall NSCLC patients in the American population could be partly resulted from the advocation of screening. In December 2013, the USPSTF first recommended lung cancer screening with CT for high-risk population meeting requisite age and smoking criteria, and subsequently, this recommendation for lung cancer screening was implemented at West China Hospital of Sichuan University, which might account for the infection point coming in 2013. Increased early-stage diagnoses could be a consequence of widespread screening. As shown in Figure 1, between 2009 and 2018, the percentage of patients with stage I lung cancer at diagnosis has dramatically increased (from 15.28% to 40.25%). From 2009 to 2013, the year-to-year percentages of patients with stage I lung cancer at diagnosis did not increase significantly (from 15.28% to 18.69%). The inflection point was identified corresponding to an accelerated increase in the rate of stage I disease diagnosed in 2013, when we started to recommend lung cancer screening. From 2014 to 2018, the percentage of stage I disease diagnosed increased annually (from 19.31% to 40.25%). The proportion of patients diagnosed with stage IV also declined extremely after 2013.

The spread of screening has led to an in-time diagnosis of early-stage lung cancer patients. We observed a gradual increase in the proportion of early-stage lung cancer patients and simultaneously a decline in advanced patients. Indeed, the past decade has also witnessed revolutions in the treatment strategies. The common surgical resection method has evolved from open surgery to minimally invasive surgery,[34] and more mature schedules for chemoradiotherapy and radiotherapy can lead to improved survival and lower side effects such as cytotoxicity.[35,36] Not only have traditional therapies improved, but novel treatment modalities and methods have emerged with the continuous efforts of clinicians and researchers. An increasing number of targeted therapy agents in lung cancer have been developed, including EGFR, ALK, and ROS1.[14] Inhibitors targeting integrins have also been applied as novel strategies for lung cancer.[37] For lung cancer patients with negative drivers or who develop resistance to molecular targeted treatment, the advent of immunotherapy, that is, to block immune checkpoints,[38] has emerged as the backbone choice for first-line therapy.[3941] Expression of PD-1/PD-L1 protein is currently playing a principal role in tumor immune evasion.[42] The anti-PD-1 drug nivolumab successfully demonstrated a pronounced extension of OS for NSCLC patients in clinical trials.[43,44] Other anti-PD-1 drugs like pembrolizumab as well as the anti-PD-L1 antibodies including atezolizumab have also shown similar survival benefits.[45,46] Immunotherapy has made it possible for advanced lung cancer patients to expect long-term survival and even a cure.[47,48] However, specifically in our research, out of 26,226 patients diagnosed with lung cancer, only a relatively limited number of advanced patients underwent genetic testing to inform targeted therapy or immunotherapy. Consequently, the use of targeted therapies led to a negligible effect on survival rates. Also, it should be noted that immunotherapy was primarily administered subsequent to 2018, and patients who received such treatment were almost rarely included in this study. Radiotherapy and chemotherapy remain predominant long-term therapeutic options for individuals with advanced lung cancer, and have experienced minimal advancements in the decade. In summary, it is our belief that while treatment developments may provide some benefit, the advantages of early diagnosis and prompt treatment in relation to lung cancer survival rates are unequivocal.

In the present analysis, we demonstrated that a substantial number of genes were critically correlated with survival, suggesting that the future generation of a nuanced prognostic model with an integration of genomic factors is feasible.[49] We identified that the EGFR, MET, and KRAS genes were significantly correlated with 5-year survival rates. For EGFR-mutated patients, the improved survival outcomes might correspond to EGFR-tyrosine kinase inhibitor (TKI) treatment.[50] Our study further stressed the need to distinguish EGFR-mutated patients from their counterparts with wild-type EGFR genotypes because of the obvious prognostic benefits potentially resulting from more precise treatment decisions. However, the clinical efficacy of EGFR-TKIs might be impaired by the amplification of the MET proto-oncogene.[51] Therefore, there might exist a codependent regulatory network of EGFR and MET, two oncogenes that our study suggested to have a prognostic impact. The specific mechanisms require further exploration. In addition, based on our aforementioned result, another significant influential gene, KRAS, was not common among our patient group, which consisted of all Chinese patients, consistent with a previous statement that KRAS was more prevalent in Western populations than in Asian populations.[52] However, despite the lower frequency, the significant survival impact suggested that it is unwise to neglect KRAS mutations in the Chinese lung cancer population.

This study had certain limitations. First, it harbored the natural limitation of a retrospective observational study and bias could be inevitable. Second, despite with large sample size, the patient population did not contain enough advanced patients who had undergone targeted therapy or immunotherapy; therefore, although the development of treatment could play a role, we still attributed the improved survival in our patient population mainly to early detection and management. Third, our exceedingly large-scale number of patients were all from a single institution and all Asians; considering the ethnic diversity, our results, especially the genomic results, have relevant but limited value for other regions. Finally, despite our careful consideration and hard efforts, this real-world research inevitably had selection bias, information bias, and confounding factors. However, despite all the limitations, our study has significantly added new insights into the current knowledge of real-world lung cancer population.

In conclusion, the current study included a valuable large-scale database of lung cancer patients. We assembled data spanning 10 years to understand the landscape of lung cancer. Our study has provided crucial clinicopathological and genomic references for lung cancer patients. Of note, the increased proportion of stage I lung cancer coincided with an improved prognosis, largely due to the recommendation of chest CT screening, indicating the significance and actual benefits of early detection and management of lung cancer in China. These results could act as a tool to empower appropriate therapeutic intervention and whole-course management of lung cancer in actual clinical practice.

Funding

This study was supported by grants from National Natural Science Foundation of China (No. 92159302), the Science and Technology Project of Sichuan (Nos. 2020YFG0473, 2022ZDZX0018, and 2023NSFSC1889), Chinese Postdoctoral Science Foundation (Nos. 2021M692309, 2022T150451), Major Program of Med-X Center for Manufacturing, Postdoctoral Interdisciplinary Innovation Fund of Sichuan University, and Postdoctoral Program of West China Hospital, Sichuan University (No. 2020HXBH084).

Conflicts of interest

None.

Supplementary Material

cm9-136-1937-s001.doc (92.5KB, doc)

Footnotes

How to cite this article: Wang CD, Shao J, Song LJ, Ren PW, Liu D, Li WM. Persistent increase and improved survival of stage I lung cancer based on a large-scale real-world sample of 26,226 cases. Chin Med J 2023;136:1937–1948. doi: 10.1097/CM9.0000000000002729

References

  • 1.Sung H Ferlay J Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021;71: 209–249. doi: 10.3322/caac.21660 [DOI] [PubMed] [Google Scholar]
  • 2.Shi JF Wang L Wu N Li JL Hui ZG Liu SM, et al. Clinical characteristics and medical service utilization of lung cancer in China, 2005-2014: Overall design and results from a multicenter retrospective epidemiologic survey. Lung Cancer 2019;128: 91–100. doi: 10.1016/j.lungcan.2018.11.031. [DOI] [PubMed] [Google Scholar]
  • 3.Cao W, Chen HD, Yu YW, Li N, Chen WQ. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin Med J 2021;134: 783–791. doi: 10.1097/cm9.0000000000001474. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Allemani C Matsuda T Di Carlo V Harewood R Matz M Nikšić M, et al. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet 2018;391: 1023–1075. doi: 10.1016/s0140-6736(17)33326-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Zeng H Chen W Zheng R Zhang S Ji JS Zou X, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries. Lancet Glob Health 2018;6: e555–e567. doi: 10.1016/s2214-109x(18)30127-x. [DOI] [PubMed] [Google Scholar]
  • 6.Aberle DR Adams AM Berg CD Black WC Clapp JD Fagerstrom RM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365: 395–409. doi: 10.1056/NEJMoa1102873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.de Koning HJ van der Aalst CM de Jong PA Scholten ET Nackaerts K Heuvelmans MA, et al. Reduced lung-cancer mortality with volume CT screening in a randomized trial. N Engl J Med 2020;382: 503–513. doi: 10.1056/NEJMoa1911793. [DOI] [PubMed] [Google Scholar]
  • 8.Wang C, Wu Y, Shao J, Liu D, Li W. Clinicopathological variables influencing overall survival, recurrence and post-recurrence survival in resected stage I non-small-cell lung cancer. BMC Cancer 2020;20: 150. doi: 10.1186/s12885-020-6621-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Jemal A Miller KD Ma J Siegel RL Fedewa SA Islami F, et al. Higher lung cancer incidence in young women than young men in the United States. N Engl J Med 2018;378: 1999–2009. doi: 10.1056/NEJMoa1715907. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Miller KD Nogueira L Mariotto AB Rowland JH Yabroff KR Alfano CM, et al. Cancer treatment and survivorship statistics, 2019. CA Cancer J Clin 2019;69: 363–385. doi: 10.3322/caac.21565. [DOI] [PubMed] [Google Scholar]
  • 11.Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer. Nature 2018;553: 446–454. doi: 10.1038/nature25183. [DOI] [PubMed] [Google Scholar]
  • 12.Cancer Genome Atlas Research Network . Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511: 543–550. doi: 10.1038/nature13385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Cancer Genome Atlas Research Network . Comprehensive genomic characterization of squamous cell lung cancers. Nature 2012;489: 519–525. doi: 10.1038/nature11404. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Tan AC, Tan DSW. Targeted therapies for lung cancer patients with oncogenic driver molecular alterations. J Clin Oncol 2022;40: 611–625. doi: 10.1200/jco.21.01626. [DOI] [PubMed] [Google Scholar]
  • 15.Le X Cornelissen R Garassino M Clarke JM Tchekmedyian N Goldman JW, et al. Poziotinib in non-small-cell lung cancer harboring HER2 exon 20 insertion mutations after prior therapies: ZENITH20-2 trial. J Clin Oncol 2022;40: 710–718. doi: 10.1200/jco.21.01323. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Bailey MH Tokheim C Porta-Pardo E, et al. Comprehensive characterization of cancer driver genes and mutations. Cell 2018;173: 371–385. doi: 10.1016/j.cell.2018.02.060. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.GBD 2019 Tobacco Collaborators . Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet 2021;397: 2337–2360. doi: 10.1016/S0140-6736(21)01169-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Shi Y Au JS Thongprasert S Srinivasan S Tsai CM Khoa MT, et al. 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: 154–162. doi: 10.1097/jto.0000000000000033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Sholl LM Aisner DL Varella-Garcia M Berry LD Dias-Santagata D Wistuba, II, et al. Multi-institutional oncogenic driver mutation analysis in lung adenocarcinoma: the lung cancer mutation consortium experience. J Thorac Oncol 2015;10: 768–777. doi: 10.1097/jto.0000000000000516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Travis WD Brambilla E Nicholson AG Yatabe Y Austin JHM Beasley MB, et al. The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol 2015;10: 1243–1260. doi: 10.1097/jto.0000000000000630. [DOI] [PubMed] [Google Scholar]
  • 21.Goldstraw P Chansky K Crowley J Rami-Porta R Asamura H Eberhardt WE, et al. The IASLC lung cancer staging project: proposals for revision of the TNM stage groupings in the forthcoming (eighth) edition of the TNM classification for lung cancer. J Thorac Oncol 2016;11: 39–51. doi: 10.1016/j.jtho.2015.09.009. [DOI] [PubMed] [Google Scholar]
  • 22.Skoulidis F, Heymach JV. Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy. Nat Rev Cancer 2019;19: 495–509. doi: 10.1038/s41568-019-0179-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Planchard D Popat S Kerr K, et al. Metastatic non-small cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2018;29: iv192–iv237. doi: 10.1093/annonc/mdy275. [DOI] [PubMed] [Google Scholar]
  • 24.Rudin CM, Brambilla E, Faivre-Finn C, Sage J. Small-cell lung cancer. Nat Rev Dis Primers 2021;7: 3. doi: 10.1038/s41572-020-00235-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Friedlaender A Subbiah V Russo A Banna GL Malapelle U Rolfo C, et al. EGFR and HER2 exon 20 insertions in solid tumours: from biology to treatment. Nat Rev Clin Oncol 2022;19: 51–69. doi: 10.1038/s41571-021-00558-1. [DOI] [PubMed] [Google Scholar]
  • 26.Cheng YI, Davies MPA, Liu D, Li W, Field JK. Implementation planning for lung cancer screening in China. Precis Clin Med 2019;2: 13–44. doi: 10.1093/pcmedi/pbz002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Jonas DE Reuland DS Reddy SM, et al. Screening for lung cancer with low-dose computed tomography: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA 2021;325: 971–987. doi: 10.1001/jama.2021.0377. [DOI] [PubMed] [Google Scholar]
  • 28.Potter AL Rosenstein AL Kiang MV Shah SA Gaissert HA Chang DC, et al. Association of computed tomography screening with lung cancer stage shift and survival in the United States: quasi-experimental study. BMJ 2022;376 e069008. doi: 10.1136/bmj-2021-069008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.GBD 2017 Risk Factor Collaborators . Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392: 1923–1994. doi: 10.1016/s0140-6736(18)32225-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Siegel RL Jacobs EJ Newton CC Feskanich D Freedman ND Prentice RL, et al. Deaths due to cigarette smoking for 12 smoking-related cancers in the United States. JAMA Intern Med 2015;175: 1574–1576. doi: 10.1001/jamainternmed.2015.2398. [DOI] [PubMed] [Google Scholar]
  • 31.Wang M Luo X Xu S Liu W Ding F Zhang X, et al. Trends in smoking prevalence and implication for chronic diseases in China: serial national cross-sectional surveys from 2003 to 2013. Lancet Respir Med 2019;7: 35–45. doi: 10.1016/s2213-2600(18)30432-6. [DOI] [PubMed] [Google Scholar]
  • 32.Sheikh M, Mukeriya A, Shangina O, Brennan P, Zaridze D. Postdiagnosis smoking cessation and reduced risk for lung cancer progression and mortality: a prospective cohort study. Ann Intern Med 2021;174: 1232–1239. doi: 10.7326/m21-0252. [DOI] [PubMed] [Google Scholar]
  • 33.Ganti AK, Klein AB, Cotarla I, Seal B, Chou E. Update of incidence, prevalence, survival, and initial treatment in patients with non-small cell lung cancer in the US. JAMA Oncol 2021;7: 1824–1832. doi: 10.1001/jamaoncol.2021.4932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Donington J, Schumacher L, Yanagawa J. Surgical issues for operable early-stage non-small-cell lung cancer. J Clin Oncol 2022; 40: 530–538. doi: 10.1200/jco.21.01592. [DOI] [PubMed] [Google Scholar]
  • 35.Chaft JE, Shyr Y, Sepesi B, Forde PM. Preoperative and postoperative systemic therapy for operable non-small-cell lung cancer. J Clin Oncol 2022;40: 546–555. doi: 10.1200/jco.21.01589. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Grønberg BH Killingberg KT Fløtten Ø Brustugun OT Hornslien K Madebo T, et al. High-dose versus standard-dose twice-daily thoracic radiotherapy for patients with limited stage small-cell lung cancer: an open-label, randomised, phase 2 trial. Lancet Oncol 2021;22: 321–331. doi: 10.1016/s1470-2045(20)30742-7. [DOI] [PubMed] [Google Scholar]
  • 37.Wang Y Hou K Jin Y, et al. Lung adenocarcinoma-specific three-integrin signature contributes to poor outcomes by metastasis and immune escape pathways. J Transl Int Med 2021;9: 249–263. doi: 10.2478/jtim-2021-0046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 2012;12: 252–264. doi: 10.1038/nrc3239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Reck M, Remon J, Hellmann MD. First-line immunotherapy for non-small-cell lung cancer. J Clin Oncol 2022;40: 586–597. doi: 10.1200/jco.21.01497. [DOI] [PubMed] [Google Scholar]
  • 40.Deng J Gao M Gou Q Xu C Yan H Yang M, et al. Organ-specific efficacy in advanced non-small cell lung cancer patients treated with first-line single-agent immune checkpoint inhibitors. Chin Med J 2022;135: 1404–1413. doi: 10.1097/cm9.0000000000002217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Zhou F, Zhou CC. Immunotherapy in non-small cell lung cancer: advancements and challenges. Chin Med J 2021;134: 1135–1137. doi: 10.1097/cm9.0000000000001338. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Doroshow DB Bhalla S Beasley MB Sholl LM Kerr KM Gnjatic S, et al. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol 2021;18: 345–362. doi: 10.1038/s41571-021-00473-5. [DOI] [PubMed] [Google Scholar]
  • 43.Brahmer J Reckamp KL Baas P Crinò L Eberhardt WE Poddubskaya E, et al. Nivolumab versus Docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med 2015;373: 123–135. doi: 10.1056/NEJMoa1504627. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Borghaei H Paz-Ares L Horn L Spigel DR Steins M Ready NE, et al. Nivolumab versus Docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl J Med 2015;373: 1627–1639. doi: 10.1056/NEJMoa1507643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Garon EB Rizvi NA Hui R Leighl N Balmanoukian AS Eder JP, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med 2015;372: 2018–2028. doi: 10.1056/NEJMoa1501824. [DOI] [PubMed] [Google Scholar]
  • 46.Rittmeyer A Barlesi F Waterkamp D Park K Ciardiello F von Pawel J, et al. Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial. Lancet 2017;389: 255–265. doi: 10.1016/s0140-6736(16)32517-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Grant MJ, Herbst RS, Goldberg SB. Selecting the optimal immunotherapy regimen in driver-negative metastatic NSCLC. Nat Rev Clin Oncol 2021;18: 625–644. doi: 10.1038/s41571-021-00520-1. [DOI] [PubMed] [Google Scholar]
  • 48.Shao J, Ma J, Zhang Q, Li W, Wang C. Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology. Semin Cancer Biol 2023;91: 1–15. doi: 10.1016/j.semcancer.2023.02.006. [DOI] [PubMed] [Google Scholar]
  • 49.Jones GD Brandt WS Shen R Sanchez-Vega F Tan KS Martin A, et al. A genomic-pathologic annotated risk model to predict recurrence in early-stage lung adenocarcinoma. JAMA Surg 2021;156: e205601. doi: 10.1001/jamasurg.2020.5601. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Ahn MJ Cho BC Ou X Walding A Dymond AW Ren S, et al. Osimertinib plus Durvalumab in patients with EGFR-mutated, advanced NSCLC: a phase 1b, open-label, multicenter trial. J Thorac Oncol 2022;17: 718–723. doi: 10.1016/j.jtho.2022.01.012. [DOI] [PubMed] [Google Scholar]
  • 51.Eser P Paranal RM Son J Ivanova E Kuang Y Haikala HM, et al. Oncogenic switch and single-agent MET inhibitor sensitivity in a subset of EGFR-mutant lung cancer. Sci Transl Med 2021;13: eabb3738. doi: 10.1126/scitranslmed.abb3738. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Reck M, Carbone DP, Garassino M, Barlesi F. Targeting KRAS in non-small-cell lung cancer: recent progress and new approaches. Ann Oncol 2021;32: 1101–1110. doi: 10.1016/j.annonc.2021.06.001. [DOI] [PubMed] [Google Scholar]

Articles from Chinese Medical Journal are provided here courtesy of Wolters Kluwer Health

RESOURCES