Association of Next Generation Sequencing and Routine Testing With Clinical Outcomes of Advanced Non-small Cell Lung Cancer Patients in a Real-world Setting

DOI: https://doi.org/10.21203/rs.3.rs-1246803/v1

Abstract

Purpose Next generation sequencing (NGS) has been used frequently in advanced non-small cell lung cancer (NSCLC) patients. Here, we investigated the treatment selections and clinical benefits of NGS technologies for patients with advanced lung cancer in a real-world setting.

Methods This retrospective study enrolled patients with advanced NSCLC who received genetic testing. Patients received either NGS or routine testing (EGFR and/or ALK and/or ROS1 only). Clinical outcomes were compared between patients received NGS and those undergoing routine testing. Propensity score analysis was used to prevent survival bias associated with patient characteristics. Overall survival (OS) was the primary outcome.

Results Of 6,451 patients with advanced NSCLC, 5,666 (87.8%) patients underwent routine testing (RT) and 785 (12.2%) were tested by NGS. The median OS was 22.6 months and the 5-year survival rate was 22.89%. Comparison of OS showed no difference according to propensity score analysis (24.8 months vs 24 months, P=0.533). With uncommon mutations, propensity score analysis showed that 1 and 2-year survival rate was significantly higher in the NGS testing group than in the routine testing group. This could be due to the higher rate of patients receiving targeted therapy (68.0% vs. 53.6%; P=0.042) and off-label drugs (28.10% vs. 11.40%; P=0.002).

Conclusion NGS was not independently with a significant benefit comparing with RT in most advanced NSCLC patients. NGS could provide clinical value for rare mutations that were not available in RT, and the future benefits of NGS in immunotherapy need to be further explored.

Introduction

The incidence of lung cancer is increasing worldwide, and non-small cell lung cancer (NSCLC) is one of the main pathological types of lung cancer (Siegel RL et al. 2020; Bade BC et al. 2020). The emergence of targetable oncogenic driver alterations, most notably epidermal growth factor receptor (EGFR) activating mutations and anaplastic lymphoma kinase (ALK) and ROS1 gene rearrangements, has transformed NSCLC treatment models by incorporating tumor genotyping into therapeutic strategies [Mitsudomi T et al. 2010; Shaw AT et al. 2014; Shaw AT et al. 2013; Peters S et al. 2017). The response rate of drugs targeting cancers harboring driver mutations is >70%, and these drugs have consistently improved patient survival outcomes. As a result, molecular testing for EGFR, ALK, and ROS1 has been recommended for all adenocarcinoma NSCLC patients since the early days of individualized precision medicine.

Advances in gene detection technology and the rapid development of new drugs have led to the identification of a growing number of driver gene mutations such as ret proto-oncogene (RET) rearrangements, neurotrophic tyrosine receptor kinase 1 (NTRK1), ERBB2 (HER2), and BRAF mutation, MET gene alterations, and other examples of actionable alterations with proven therapeutic options (Lindeman NI et al. 2018; Salama AKS et al. 2020; Koga T et al. 2018; Farago AF et al. 2015; Yang H et al. 2020; Passiglia F et al. 2020). Companion diagnostic tests for gene mutations that impact the success of anticancer drugs were conducted separately for each mutation, which detected EGFR, ALK, and ROS1 as the main genes. Although the incidence of rare driver gene mutations (mutation rate <5%) such as those of MET, BRAF, NTRK, and HER2 is relatively low and may vary according to ethnic differences, agents targeting these driver mutations are being developed, and the number of emerging biomarkers and targets continues to grow. Consequently, and increasing number patients undergo multigene sequencing of tumors to identify genomic alterations that can be effectively targeted, and many clinicians are using next generation sequencing (NGS) methods to detect gene mutations associated with lung cancer treatment.

Studies have demonstrated the feasibility of routine NGS detection in patients with NSCLC, and showed that genetic testing using NGS is useful for the design of lung cancer treatment strategies (Zehir A et al. 2017; Kris MG et al. 2014; Yamamoto G et al. 2017; Tan DS et al. 2016). Presley et al compared survival outcomes between patients with advanced NSCLC who received broad-based genomic sequencing and those who received routine testing for EGFR mutations and/or ALK rearrangements alone in the Community Oncology Setting (Presley CJ et al. 2018). They showed that broad-based genomic sequencing provided direct information on treatment in a minority of patients. Singal et al assessed whether a database with comprehensive genomic profiling could identify and extend associations in NSCLC, and the results demonstrated the feasibility of creating a clinicogenomic database derived from routine clinical experience (Singal G et al. 2019). Therefore, whether NGS can bring survival benefits to patients compared with routine testing remains controversial. The paucity of appropriate studies and the incomplete understanding of genomic architecture across Chinese populations are additional challenges.

In this study, routine testing (EGFR and/or ALK and/or ROS1 only) was compared with NGS panel testing to identify the optimal strategy. We analyzed the difference in the survival benefit between patients with advanced NSCLC who used NGS and those undergoing routine testing as well as the potential effect of each test on therapeutic strategies.

Methods

Study design

This retrospective cohort study used the Database of Zhejiang Cancer Hospital to identify patients diagnosed with stage IIIB/IV advanced NSCLC who received antineoplastic treatment and either next generation sequencing (NGS) or routine testing (EGFR and/or ALK and/or ROS1 only). The histological classification of NSCLC was based on the World Health Organization criteria (2015 version) (Travis WD et al. 2015). Various panels for NGS were used, but all of them included the nine genes used as molecular biomarkers in the National Comprehensive Cancer Network (NCCN) guidelines list of driver mutations (EGFR, ALK, ROS1, KRAS, HER2, BRAF, MET, RET, and NTRK). Propensity score-matched survival analysis was used to evaluate differences in overall survival (OS) between the groups. The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.  

Study sample

Patients with advanced NSCLC who were diagnosed between January 1, 2013 and June 30, 2019 and had genetic testing results were included in the study. The cohort included patients with advanced NSCLC or early-stage NSCLC that subsequently developed recurrent or progressive disease during the period. Each patient had a diagnosis of lung cancer, at least two documented clinical visits on or after January 1, 2011, pathology consistent with non-squamous NSCLC, and confirmation of advanced NSCLC on or after January 1, 2011. Patients with evidence of other concurrent active cancers within 6 months prior to diagnosis of advanced NSCLC, other than non-melanoma skin cancer, were excluded. Patients with ever NGS testing NGS (include at least EGFR, ALK, ROS1, KRAS, HER2, BRAF, MET, RET, and NTRK) were considered the treatment group, whereas patients with only routine testing for EGFR/ALK/ROS1 were considered as the control group in this study. Patients who met the following inclusion criteria were included in the study: 1) recorded clinicopathological information, including age and sex; and clinical data, such as pathological typing, genetic testing results and treatment type; 2) pathological examination of tumor specimens with proven records of at least one common driver gene test (EGFR or ALK or ROS1); 3) all patients received at least one line of systemic antineoplastic treatment for advanced NSCLC. Patients were excluded if: (1) clinical data including age, gender, and stage were missing; (2) pathologic examination showed NSCLC NOS or small cell lung cancer; (3) follow-up survival results were missing. 

Outcomes

The last follow-up date of the study was November 30, 2021. OS was defined as the time from the start of first-line treatment to the date of death. Analysis was performed using 12-month or 24-month mortality. OS was used as the outcome in the propensity score-matched survival analysis. Secondary outcomes included genetic alterations and treatments received.  

Statistical analysis 

The χ2 test was used for comparison of the distribution of cohort characteristics and treatment types between the NGS group and routine testing group. Propensity score matching was used to address potential confounding due to the significantly different cohort characteristics. Multivariable logistic regression analysis was used to estimate the propensity score based on age, sex, smoking status, stage, year of diagnosis, EGFR or ALK mutation, comorbidity, a single line of treatment, and immunotherapy in line 1 or line 2 vs. line 3 or line 4 of treatment. The quality of data for each variable was considered before their inclusion in propensity score-matched survival analysis. According to the study by Presley et al and to prevent survival bias caused by certain patient characteristics, six covariates were set as exact covariate matches as follows: EGFR or ALK mutation, receipt of only one line of treatment, year of diagnosis, receipt of immunotherapy in line 1 or line 2 of treatment, and receipt of immunotherapy in line 3 or line 4 of treatment. For the variables with missing data (smoking status, and EGFR or ALK mutation), a dummy variable was used because the missing variables were not missing at random [17]. One-to-one matching was performed using a nearest neighbor algorithm with ratio of 1 and a caliper of 0.01 standard deviation. Survival outcomes were estimated and compared by the Kaplan-Meier method (time 0 = start of first line treatment) and the log-rank test. Median survival and hazard ratio (HR) (log rank) and 95% confidence interval (CI) were reported. All statistical tests were two-sided, and a P value <0.05 was considered statistically significant. R version 3.6.0 (R-project, Institute for Statistics and Mathematics: packages MatchIt V3.0.2) was used for all analyses.

Results

Baseline characteristics 

Of 6,451 patients diagnosed with advanced NSCLC, 785 (12.2%) received NGS testing (Table 1). The median age at diagnosis was 61 years (range, 19–90 years), 45.2% of patients had a history of smoking, and 41.6% of patients were female.  

Table 1 

Characteristics of the sample of patients with advanced non–small cell lung cancer (N = 6451)

 

Total

No. (%)

P Value

NGS (n=785)

Routine Testing (n=5666)

Age at diagnosis, y

 

≤45

68(8.7)

388(6.8)

 

 

0.007

46-55

215(27.4)

1330(23.5)

56-65

308(39.2)

2249(39.7)

66-75

165(21.0)

1450(25.6)

≥76

29(3.7)

249(4.4)

Sex

 

Male

433(55.2)

3334(58.8)

 

0.050

Female

352(44.8)

2332(41.2)

Comorbidity countb

 

0

513(65.4)

2794(49.3)

 

<0.0001

1-2

266(33.8)

2660(47.0)

≥3

6(0.8)

212(3.7)

Smoking statusc

 

No history of smoking

435(55.4)

2896(51.1)

 

<0.0001

History of smoking

346(44.1)

2574(45.4)

Unknown

4(0.5)

196(3.5)

 

Medical payment method

 

city

358(45.6)

2474(43.6)

 

0.001

 

country

115(14.6)

1185(20.9)

self-paying

      2(0.3)

9(0.2)

Unknown

310(39.5)

1998(35.3)

 

Income, by medical payment method

 

1 (lowest)

117(14.9)

1194(21.0)

<0.0001

2(highest)

            358(45.6)

2474(43.7)

Unknown

310(39.5)

1998(35.3)

 

Stage at diagnosis

 

I

15(1.9)

208(3.7)

 

<0.0001

II

15(1.9)

214(3.8)

III

93(11.8)

1071(18.9)

IV

662(84.4)

4173(73.6)

Year of diagnosis

 

2013

0(0)

588(10.4)

 

 

<0.0001

2014

13(1.7)

785(13.9)

2015

29(3.7)

987(17.4)

2016

156(19.9)

1062(18.7)

2017

224(28.5)

1051(18.6)

2018

259(33.0)

920(16.2)

2019

104(13.2)

273(4.8)

Timing of next generation sequencing 

Before first-line treatment

522(66.5)

 

 

Before second-line treatment

165(21.0)

 

 

Before third-line treatment

51(6.5)

 

 

Before fourth-line treatment

20(2.5)

 

 

Before fifth-line treatment

3(0.4)

 

 

Before sixth-line treatment

2(0.3)

 

 

Other

22(2.8)

 

 

Survival analysis

All survival analyses were performed using the Kaplan-Meier method. For the entire cohort, the median OS was 22.6 months and the 5-year survival rate was 22.89%. There was a significant difference in survival between patients who received targeted therapy and those who did not in the unadjusted survival curves (HR, 0.52 [95% CI, 0.49–0.56]; log-rank P < 0.0001; Fig. 1A) or among the 2177 matched pairs with well-matched characteristics and balance in the propensity score analysis (HR, 0.56 [95% CI, 0.52–0.60]; log-rank P < 0.0001; Fig. 1B).  

Survival of patients with NGS testing and routine testing

OS was compared between patients who underwent NGS testing and those who underwent routine testing. In the unadjusted survival curves, there was an absolute difference between the two cohorts (HR, 0.87 [95% CI, 0.78–0.96]; log-rank P = 0.0097; Fig. 2A). In the propensity score analysis, there was no obvious OS difference between the two cohorts (760 matched patients; HR, 0.95 [95% CI, 0.82–1.11]; log-rank P = 0.53; Fig. 2B). Patients who received NGS had a significantly higher 1-year survival rate than that of patients with routine testing (HR, 0.66 [95% CI, 0.53–0.83]; log-rank P = 0.0004), as well as a higher rate of patients receiving targeted therapy (68.0% vs. 53.6%; P < 0.0001; Fig. 3A and 3B) and patients receiving off-label drugs (28.10% vs. 11.40%; P < 0.0001; Fig. 3C and 3D). The NGS testing cohort had a greater number of different types of off-label drugs. 

Survival of patients with uncommon mutations

In NSCLC, common mutations include EGFR 19del and L858R mutations, and ALK and ROS1 fusion. Here, we defined mutations other than these common mutations as uncommon mutations. In patients with uncommon mutations, OS was compared between patients who received NGS testing and those who underwent routine testing. There was an absolute difference between the two cohorts (HR, 0.79 (95% CI, 0.69–0.91); log-rank P = 0.0038; Fig. 4A) in the unadjusted survival curves. After using the propensity score analysis, the OS of these patients was not significantly different (HR, 0.86 [95% CI, 0.69–1.08]; log-rank P = 0.19; Fig. 4B). The 12-month mortality between the two cohorts in 314 matched pairs was significantly different (HR, 0.72 [95% CI, 0.54–0.97]; log-rank P = 0.03) (Supplementary Fig. 1).

Next, the patients were divided into four groups: patients with uncommon mutations who received NGS, those who received routine testing, those who received targeted therapies, and those who did not receive targeted therapies. The results of unadjusted survival curves showed that the median OS was longer in the two groups with targeted therapies, especially in the groups with NGS testing (Supplementary Fig. 2). Among uncommon mutation patients with targeted therapies, propensity score analysis showed that the 1 and 2-year survival rate was significantly higher in the NGS testing group than in the routine testing group (Supplementary Fig. 2). This suggested that NGS was a better detection method for patients with uncommon mutations. This could be associated with the fact that the rate of off-label treatments was significantly higher in the NGS group than in the routine testing group (45.4% vs. 9.6%; P < 0.0001; Supplementary Fig. 3), and indicated that NGS testing resulted in a more objective and precise clinical therapy for uncommon mutation patients.  

Treatments received

All patients received first-line treatment, and 3,517 (54.52%) and 1,326 (20.56%) received second- and third-line treatments, respectively. Patients receiving NGS testing were more likely to receive targeted therapy (51.7%) as first-line treatment than routine testing patients (34.6%, P < 0.0001), whereas the opposite result was obtained for second-line treatment (19.8% for NGS testing vs. 25.1% for routine testing; P = 0.012; Table 2) and for third-line treatment (12.9% vs. 15.4%; P = 0.333). The rate of chemotherapy ± anti-VEGF treatment as first-line treatment was lower in the NGS testing group than in the routine testing group (39.5% vs. 62.5%; P < 0.0001), whereas it was similar between the two cohorts in the second- and third-line treatments. In the first-, second- and third-line therapy groups, patients receiving NGS testing were more likely to receive immunotherapy (1st-line: 3.6% vs. 1.0%; 2nd-line: 8.3% vs. 2.8%; 3rd-line: 4.6% vs.1.8%) or participate in clinical trials (1st-line: 5.2% vs. 1.9%; 2nd-line: 5.7% vs. 3.0%; 3rd-line: 2.5% vs.1.7%) than those receiving routine testing (Table 2). Among patients without EGFR mutations or ALK fusions, the percentage receiving targeted therapies, immunotherapy, and clinical trials was higher in the NGS testing group than in the routine testing group. Correspondingly, the percentage receiving chemotherapy ± anti-VEGF treatment showed the opposite trend (Table 3).

Table 2 

Treatments received by patients with advanced non–small cell lung cancer.

 

 

No. (%)

 

 

Treatment Type

NGS

(n = 785)

Routine Testing

(n =5666)

 

Valueb

 

First-line treatment

 

Targeted treatment

406 (51.7)

1961(34.6)

<0.0001

 

Chemotherapy ± anti-VEGF

310 (39.5)

3541(62.5)

<0.0001

 

Immunotherapy

28 (3.6)

55(1.0)

<0.0001

 

Clinical trial

41 (5.2)

109(1.9)

<0.0001

Second-line treatment

 

Targeted treatment

98(19.8)

758(25.1)

0.012

 

Chemotherapy ± anti-VEGF

327(66.2)

2088(69.1)

0.201

 

Immunotherapy

41 (8.3)

84(2.8)

<0.0001

 

Clinical trial

28 (5.7)

93(3.0)

0.003

Third-line treatment

 

Targeted treatment

31(12.9)

167(15.4)

0.333

 

Chemotherapy ± anti-VEGF

192(80.0)

881(81.1)

0.689

 

Immunotherapy

11(4.6)

20(1.8)

0.011

 

Clinical trial

6(2.5)

18(1.7)

0.376

Fourth-line treatment

 

Targeted treatment

31(12.9)

167(15.4)

0.333

 

Chemotherapy ± anti-VEGF

192(80.0)

881(81.1)

0.689

 

Immunotherapy

11(4.6)

20(1.8)

0.011

 

Clinical trial

6(2.5)

18(1.7)

0.376

Total NGS

785(100)

 

 

 

No NGS–informed targeted treatment

251(31.9%)

 

 

 

Other targeted treatment

40(5.0%)

 

 

 

EGFR/ALK approved targeted treatment

382(48.7%)

 

 

 

EGFR/ALK off-label treatment

112(14.3%)

 

 


Table 3

 First and second line treatment type received among patients without EGFR or ALK alterations

Treatment Type

 

NGS

Routine testing

 

P-value

 

n

%

n

%

 

First Line Treatment

 

 

 

 

 

  Targeted Treatment

42

12.9

201

8.5

0.009

  Chemo +/- Anti-VEGF

230

70.7

2057

87.1

<0.0001

  Immunotherapy

25

7.8

45

1.9

<0.0001

  Clinical Trial

28

8.6

60

2.5

<0.0001

Second Line Treatment

 

 

 

 

 

  Targeted Treatment

55

27.2

224

20.1

0.022

  Chemo +/- Anti-VEGF

102

50.5

793

71.1

<0.0001

  Immunotherapy

33

16.4

62

5.6

<0.0001

  Clinical Trial

12

5.9

36

3.2

0.058

Discussion

Two different survival analysis methods were used to show that NGS detection technology based on accessible targeted therapy could extend the overall survival of patients with advanced NSCLC by nearly 3 months compared with routine detection technology in the Chinese population. Propensity score analysis showed NGS technology was not independently associated with better survival compared with routine testing. However, propensity score analysis confirmed the significant difference in the 1-year survival rate between the two groups. These differences may be attributed to the higher proportion of patients receiving targeted therapy and off-label treatment in the NGS group than in the routine testing group. However, we also need to consider the availability of targeted drugs in China.

Genotyping is an essential step for the selection of targeted regimens in lung cancer, especially in lung adenocarcinoma. The survival benefits of targeted therapy are higher than those of chemotherapy in patients with lung cancer. The present results showed that there was a significant difference in survival between patients with and without targeted therapy. The median OS of NSCLC patients treated with targeted therapy was 30 months, and the 5-year survival rate was 29.6% in this study. These findings are consistent with the results of previous studies and suggested that driver and genotype-directed therapy improved the survival of patients (Kris MG et al. 2014; Singal G et al. 2019). Comprehensive survival analysis of patients receiving NGS and routine testing was performed to explore the difference between the two techniques in clinical practice. The results showed a difference in OS between patients detected by NGS and routine testing; the OS of NSCLC patients in the NGS group was 2.7 months longer than that of the routine detection group (P = 0.0097). In particular, the 1-year survival rate was significantly higher in the NGS group than in the routine testing group (82.03% vs. 70.76%, P༜0.0001). This may be related to the obviously higher rate of patients who received targeted therapy. However, propensity score analysis showed no difference in OS between the two groups, and the 5-year survival did not differ significantly, which was consistent with previous data (Kris MG et al. 2014). The use of NGS in patients with advanced NSCLC is already fully endorsed in many international guidelines. According to previous reports, the value of routine testing and NGS testing is still controversial. Singal et al demonstrated the feasibility of creating a comprehensive genomic profiling derived from routine clinical experience and the use of large-scale clinicogenomic data sets can augment various stages of drug development (Singal G et al. 2019). Presley et al demonstrated that broad-based genomic sequencing was not associated with better survival compared with routine testing among patients with advanced NSCLC receiving treatment (Presley CJ et al. 2018). Similar results were obtained in the present study, which showed no obvious OS difference using propensity score analysis (P = 0.53). This may indicate that the overall survival benefit of NGS in lung adenocarcinoma patients is not large, and a specific population is necessary to regulate the detection by NGS.

NGS may increase the opportunities for targeted therapies. Wu et al described the Pan-Asian guidelines established by ESMO and the Chinese Society of Clinical Oncology recommending testing of all advanced non-squamous NSCLC patients for EGFR mutation, ALK rearrangement, ROS1 rearrangement, and BRAF mutation (Wu YL et al. 2019). The IALSC Updated Molecular Testing Guidelines recommend testing for EGFR, ALK, and ROS1 along with the inclusion of additional genes (ERBB2, MET, BRAF, KRAS, and RET) for NGS panels (Lindeman NI et al. 2018). These findings suggest that NGS testing is becoming increasingly important for confirming the genetic features of patients, and effective targeted drugs may be needed to demonstrate the improved outcomes of NSCLC patients using NGS. However, only three categories of targeted drugs (EGFR, ALK, and ROS1) have been approved in China, and access to other drugs is limited. In this study, NGS testing was not superior for guiding targeted therapy in second- and third-line treatments, which may be due to the limited targeted drugs against EGFR mutations or ALK fusions that can be easily checked by routing testing. NGS is used in second- and third-line treatments to explore drug resistance mechanisms, as the corresponding targeted drugs are limited. Therefore, the proportion of off-label patients increased after NGS testing in China.

NGS testing can identify specific mutations that cannot be found by routine testing. In the present study, the OS of uncommon mutation patients and that of patients receiving targeted therapies with NGS testing was significantly longer than that of patients with routine testing. On the other hand, the rate of off-label treatments was significantly higher in the NGS than in the routine testing group (45.4% vs. 9.6%; P <0.0001), suggesting that NGS testing resulted in a more objective and precise clinical therapy for patients with uncommon mutations. Moreover, off-label using has to be more targeted based on NGS testing rather than abuse. In addition, NGS may help patients with specific mutations participate in clinical trials (9.6% vs. 3.9%). Zehir et al established a large-scale, prospective clinical sequencing initiative using a comprehensive assay (MSK-IMPACT trial), and found that only 11% of patients were enrolled in genomic-matched clinical trials among 10,000 patients (Zehir A et al. 2017). In the present study, the proportion of patients matched to clinical trials based on NGS was 9.6%, which was slightly lower than that of the previous study. This may be because clinical trials in China were somewhat similar to foreign community models. The study of Presley et al focused mainly on community-based practice, and demonstrated that the number of patients treated in the community setting who have access to clinical trials for advanced NSCLC remained low (Presley CJ et al. 2018). A previous study explored changes in clinical trials of cancer drugs in China over the decade of 2009–2018, and the results showed an increase in the number of clinical trials over time (Li N et al. 2019). The proportion of Phase 1 trials being initiated increased as well. However, the number of clinical trials focusing on epidemiological characteristics unique to the Chinese population remains low, and the geographical distribution of leading clinical trial units is unbalanced. Therefore, increased access to research clinical trials in China may improve the use of mutational data by NGS testing. The crossover of survival analysis curves of NGS and routine testing may be due to the fact that NGS panels derived from routine clinical practice may be mixed, and some patients cannot afford expensive targeted drugs, or the conditions were not met for inclusion in clinical studies. Overall, although the benefits of NGS for NSCLC patients are limited, NGS remains essential in clinical practice.

The present study had several limitations, which need to be considered for data interpretation. First, this was a retrospective study, which may affect the results. For example, patient heterogeneity, inconsistency of treatment options selected by clinicians, and the fact that not all patients received NGS detection at diagnosis were factors that need to be considered. Second, this was not a randomly assigned study and this may induce analysis bias. Third, other outcome points including overall response rate and progression-free survival were not analyzed in this study. Fourth, despite the propensity analysis, confounding factors were not fully excluded, and unknown confounding factors may have been included. For patients undergoing NGS testing, the NGS panel contained the gene mutations or tumor mutation burden (TMB) mentioned in the NCCN guidelines; however, the panels were derived from different testing platforms and were not all the same. We considered that our study still had some clinical significance. Our article conducted out a large sample to confirm the NGS value compared by routine testing and it also suggest that NGS may need to be used more accurately. Future studies should assess the value of NGS in clinical trials of new drugs and the benefits of NGS in clinical practice after the approval of new drugs and immunotherapy.

Conclusion

NGS technology was not independently associated with better survival compared with routine testing. NGS has some value in the detection of uncommon driver mutations, which may lead to a greater benefit from targeted treatments and participation in clinical trials or guiding some appropriate off-label medications. The patient populations need to be further categorized to explore the value of NGS in clinical practice.

Declarations

Author contributions 

SZB, ZYP designed this study; WWX, SZB, ZXY prepared and wrote the manuscript. SJF, LGY, SZY, SL collected samples and clinical data. WWX, ZXY, MTH performed data analysis; SZB, ZYP revised the manuscript. All authors have read and approved the final manuscript. 

Funding 

This study was funded by the Zhejiang Chinese Medical Science and Technology Foundation (No.2021ZQ013) and Xisike-Hanson Cancer Research Foundation (Y-HS2019-20) and Huilan Public-Hanson Pharmaceutical Lung Cancer Precision Medical Research Special Fund Project Foundation (HL-HS2020-5). 

Data availability 

Data and materials are available on request. 

Conflicts of Interest 

Xiaoyan Zhang and Tonghui Ma are the employees of Genetron Health (Beijing) Technology, Co. Ltd., China. All other authors declare no competing interests. 

Ethics approval 

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Review Board of Zhejiang Cancer Hospital and by the Ethics Committee of Zhejiang Cancer Hospital.  

Consent to participate 

Since this was a non-interventional, retrospective study, informed consent was obtained whenever possible, but was not required for every participant. 

Consent for publication 

Not applicable

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