Abstract
Immune checkpoint inhibitors (ICIs) in conjunction with chemotherapy (IC), bevacizumab in conjunction with chemotherapy (AC), and ICI in conjunction with chemotherapy and bevacizumab (IAC) are all used as initial therapies for metastatic lung adenocarcinoma with driver gene negativity. Few studies have investigated which treatment regimen is more efficacious in the Chinese population. Data from metastatic lung adenocarcinoma patients with driver gene negativity at the Affiliated Hospital of Qingdao University were retrospectively collected. The propensity score matching approach was used to pair the patients. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan–Meier curves. Independent factors affecting PFS and OS were determined using the Cox proportional hazards model. A total of 119 patients were enrolled in this study. After propensity score matching, the PFS of patients treated with IAC was substantially lengthier than that of patients treated with AC (median PFS, 15.8 vs 8.5 months; P = .0057). The IAC group owned lengthier PFS than the IC group, nonetheless the difference was not regarded as statistically significant. The PFS in the IC group did not differ substantially from that in the AC group. IAC had a longer OS than AC (median OS [mOS]: 35.9 vs 26.9 months; P = .021). The OS of IAC was numerically prolonged compared with that of IC, but not statistically different. Statistical differences were not observed between the OS of the IC and AC groups. The COX analysis showed that therapy and efficacy to complete response/partial response independently influenced on PFS and OS, and age independently influenced on PFS. No differences in adverse events were observed among the 3 groups. IAC may be the best initial therapy option for patients with metastatic lung adenocarcinoma with driver gene negativity.
Keywords: bevacizumab, chemotherapy, driver gene negativity, efficacy, immune checkpoint inhibitors, initial therapy, lung adenocarcinoma
1. Introduction
Lung cancer has the 2nd and 1st highest incidence and mortality rates among all types of cancer globally, respectively.[1] Eighty-five percent of all lung cancer cases are non-small cell lung cancer (NSCLC).[2] The majority of NSCLC are diagnosed with metastasis and have poor outcomes, with a median overall survival (mOS) of less than 1 year.[3] In recent years, significant progress has been made in the screening, diagnosis, and therapy of NSCLC, particularly in systemic therapies, including targeted drugs, immune checkpoint inhibitors (ICIs), and angiogenesis inhibitors, resulting in a marked improvement in patient prognosis.[4] The effectiveness of bevacizumab has been proven in the treatment of a wide range of cancers, including non-squamous NSCLC, metastatic colorectal, cervical, and ovarian cancers.[5] A phase 3 trial on Chinese patients with metastatic non-squamous NSCLC confirmed that the bevacizumab plus chemotherapy (carboplatin/paclitaxel) group owned longer progression-free survival (PFS) and overall survival (OS) than the chemotherapy (carboplatin/paclitaxel) group.[6] In recent years, ICIs have been utilized for the treatment of a variety of cancers. By alleviating tumor-induced suppression, ICIs promote the activation, proliferation, and differentiation of T-lymphocytes, ultimately enhancing the anti-tumor immune response.[7] Programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) inhibitors, which are ICIs, have shown promising efficacy against a variety of cancers.[8] In metastatic NSCLC patients with driver gene negativity, ICIs substantially prolonged the PFS and OS.[9] Both PD-1 inhibitor combination chemotherapy (IC) and bevacizumab combination chemotherapy (AC) are recommended by the Chinese guidelines as initial therapies for metastatic non-squamous NSCLC with driver gene negativity.[10] The IMpower150 study, conducted on advanced non-squamous NSCLC patients without epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutations, demonstrated that the atezolizumab combined with chemotherapy and bevacizumab (ABCP) group had significantly longer PFS than the bevacizumab in conjunction with chemotherapy (BCP) group (median PFS [mPFS]: 8.3 vs 6.8 months; hazard ratio [HR]: 0.62; 95% confidence interval [CI]: .52–.74; P < .001), and the mOS of the ABCP group was substantially extended compared to that of the BCP group (19.2 vs 14.7 months; HR: .78; 95% CI: .64–.96; P = .02), with consistent improvements in final OS outcomes (mOS: 19.5 vs 14.7 months; HR = .80; 95% CI: .67–.95).[11,12] Based upon the findings from the IMpower150 study, the National Comprehensive Cancer Network guideline has recommended atezolizumab coupled with bevacizumab, paclitaxel, and carboplatin as initial therapy for advanced non-squamous NSCLC patients with driver gene negativity.[13] Atezolizumab is a PD-L1 inhibitor, and fewer studies have evaluated the efficacy of PD-1 inhibitors coupled with bevacizumab and chemotherapy (IAC), AC and IC in the Chinese population. Presently, PD-1 inhibitors in China, including camrelizumab, sintilimab, tislelizumab, and toripalimab, have shown efficacy in patients with metastatic non-squamous NSCLC and are recommended by Chinese clinical guidelines.[10] In our study, 119 patients with driver gene-negative metastatic lung adenocarcinoma were analyzed to clarify the efficacy of IAC, AC, and IC and to provide a reference for subsequent clinical practice.
2. Materials and methods
2.1. Patients
Metastatic lung adenocarcinoma patients with driver gene negativity from the Affiliated Hospital of Qingdao University during the period January 1th, 2019 until December 30th, 2023 were included in our study. The last follow-up was May 30th, 2024. The criteria for inclusion: patients with pathologically diagnosed lung adenocarcinoma; patients with complete case information; patients treated with complete 1st-line IAC, AC, or IC regimens; patients with measurable lesions; patients with an Eastern Cooperative Oncology Group score of 0 to 1; patients without EGFR and ALK mutations. The criteria for exclusion: patients with second primary cancer; patients with autoimmune diseases, including vitiligo and psoriasis; patients lost to follow-up.
We collected clinical data of patients, including sex, age, smoking history, site of metastasis, PD-L1 expression value, TP53 and KRAS mutation status. A week before the patient’s 1st treatment, blood lactate dehydrogenase (LDH) levels were collected. PD-L1 expression values were measured by immunohistochemistry 22C3 method and scored using the tumor proportion score.
2.2. Treatments
All patients were divided into 3 groups based upon the treatment regimens: AC group, chemotherapy in combination with bevacizumab, following 4 to 6 cycles of treatment, maintenance therapy with bevacizumab was prescribed; IC group, chemotherapy in combination with ICI, following 4 to 6 cycles of treatment, maintenance therapy with ICI was prescribed; IAC group, chemotherapy in combination with ICI and bevacizumab, following 4 to 6 cycles of treatment, maintenance therapy with bevacizumab and ICI was prescribed. First, chemotherapy: pemetrexed in combination with platinum every 3 weeks. Second, ICIs, including camrelizumab, sintilimab, tislelizumab, and toripalimab, are PD-1 inhibitors. The dose of camrelizumab, sintilimab, and tislelizumab was 200 mg once every 3 weeks. Each dose of toripalimab was 240 mg once every 3 weeks. Third, bevacizumab: 10 mg/kg every 3 weeks. Ethics committee of the Affiliated Hospital of Qingdao University examined and authorized our study (approval number: QYFYWZLL29230). As this was a review study, written informed consent was not required.
2.3. Efficacy and follow-up
OS and PFS were set as primary end-points, with objective response rate (ORR), 6- and 12-month PFS rates, and 12- and 36-month OS rates as secondary end-points. Efficacy was evaluated based upon the Response Evaluation Criteria in Solid Tumors version 1.1.[14] Imaging was performed every 6 to 8 weeks to evaluate efficacy and after 6 months, every 2 months. OS was the duration from the initial therapy to death, or the end of follow-up. PFS was the duration from initial therapy to progressive disease (PD), death, or the end of follow-up. ORR is the sum of the proportions of complete response (CR) and partial response (PR).
2.4. Adverse events (AEs)
The common terminology criteria for AEs (CTCAE version 5.0) was utilized to evaluate AEs.
2.5. Statistical analysis
To control for confounders and selection bias, the patients were paired using propensity score matching (PSM). The sample size required in the study was analyzed using the pwr package (effect size f = 0.4, statistical test power 1 − β = 0.8, and significance level α = 0.05), and the results showed that a sample size of at least 21 cases was required for each group. Categorical variables, represented as counts and proportions, were compared utilizing the chi-square test. Continuous variables, represented as mean, standard deviation, median, and interquartile range, were compared utilizing Student t test. OS and PFS were evaluated with Kaplan–Meier survival analysis, and intergroup comparisons were conducted employing the log-rank test. Univariate and multivariate Cox analysis were utilized to determine the independent influences on OS and PFS. Multivariate Cox analysis was performed on those variables that had P < .2 in the univariate Cox analysis. P < .05 represented statistically significant difference. R (version 4.3.1; R Foundation for Statistical Computing, Vienna, Austria) and SPSS 27.0 software (IBM Corp, Armonk) were used for data and image generation processing.
3. Results
3.1. Characteristics of patients
One hundred nineteen patients with metastatic lung adenocarcinoma were included in our study (Fig. 1). The median age of patients was 64 years, male patients made up the majority of patients (78.2%), 65.5% had a history of smoking, and lung metastasis was the most common (45.4%), following bone metastasis (34.5%), brain metastases (20.2%), and the lowest rate of liver metastases (10.9%). There was no information available on the status of PD-L1 in 43 patients, as well as the mutation status for TP53 and KRAS in 39 patients. Of the 119 patients, the AC group had 41 patients, the IC group had 44, and the IAC group had 34. Table 1 shows the characteristics of patients. The 2 characteristics of brain metastasis and TP53 status were unbalanced between the AC and IAC groups, as well as between the IC and IAC groups, and PD-L1 expression status was unbalanced between the AC and IC groups. PSM was used to match patients (using the nearest-neighbor method and 1-to-1 matching) to equalize baseline characteristics. After PSM, the IAC and AC groups were matched for 34 pairs of patients, the IAC and IC groups were matched for 34 pairs of patients, and the IC and AC groups were matched for 41 pairs of patients. All the characteristics were balanced (Table 2).
Figure 1.
Flowgraph of this study.
Table 1.
Clinical characteristics of patients.
| All (N = 119) |
AC (N = 41) |
IC (N = 44) |
IAC (N = 34) |
P (AC vs IC) | P (AC vs IAC) | P (IC vs IAC) | |
|---|---|---|---|---|---|---|---|
| Sex, n (%) | .664 | 1 | .766 | ||||
| Male | 93 (78.2%) | 31 (75.6%) | 36 (81.8%) | 26 (76.5%) | |||
| Female | 26 (21.8%) | 10 (24.4%) | 8 (18.2%) | 8 (23.5%) | |||
| Age, yr, Median (IQR) |
64.0 [59.0–69.0] | 62.0 [55.0–68.0] | 65.5 [59.8–71.0] | 65.0 [60.0–69.8] | .077 | .226 | .754 |
| Smoking, n (%) | .357 | .567 | .985 | ||||
| No | 41 (34.5%) | 17 (41.5%) | 13 (29.5%) | 11 (32.4%) | |||
| Yes | 78 (65.5%) | 24 (58.5%) | 31 (70.5%) | 23 (67.6%) | |||
| Bone metastasis, n (%) | .250 | .758 | .607 | ||||
| No | 78 (65.5%) | 24 (58.5%) | 32 (72.7%) | 22 (64.7%) | |||
| Yes | 41 (34.5%) | 17 (41.5%) | 12 (27.3%) | 12 (35.3%) | |||
| Brain metastasis, n (%) | .900 | .038 | .012 | ||||
| No | 95 (79.8%) | 35 (85.4%) | 39 (88.6%) | 21 (61.8%) | |||
| Yes | 24 (20.2%) | 6 (14.6%) | 5 (11.4%) | 13 (38.2%) | |||
| Liver metastasis, n (%) | .733 | 1 | .723 | ||||
| No | 106 (89.1%) | 36 (87.8%) | 40 (90.9%) | 30 (88.2%) | |||
| Yes | 13 (10.9%) | 5 (12.2%) | 4 (9.09%) | 4 (11.8%) | |||
| Lung metastasis, n (%) | .343 | .899 | .606 | ||||
| No | 65 (54.6%) | 20 (48.8%) | 27 (61.4%) | 18 (52.9%) | |||
| Yes | 54 (45.4%) | 21 (51.2%) | 17 (38.6%) | 16 (47.1%) | |||
| PD-L1 expression, n (%) | .015 | .087 | .443 | ||||
| <1% | 37 (31.1%) | 12 (29.3%) | 11 (25.0%) | 14 (41.2%) | |||
| 1–49% | 16 (13.4%) | 4 (9.76%) | 8 (18.2%) | 4 (11.8%) | |||
| ≥50% | 23 (19.3%) | 3 (7.32%) | 13 (29.5%) | 7 (20.6%) | |||
| Unknown | 43 (36.1%) | 22 (53.7%) | 12 (27.3%) | 9 (26.5%) | |||
| TP53 mutation, n (%) | .112 | .037 | .034 | ||||
| No | 55 (46.2%) | 25 (61.0%) | 18 (40.9%) | 12 (35.3%) | |||
| Yes | 25 (21.0%) | 6 (14.6%) | 6 (13.6%) | 13 (38.2%) | |||
| Unknown | 39 (32.8%) | 10 (24.4%) | 20 (45.5%) | 9 (26.5%) | |||
| KRAS mutation, n (%) | .122 | .963 | .227 | ||||
| No | 58 (48.7%) | 23 (56.1%) | 17 (38.6%) | 18 (52.9%) | |||
| Yes | 22 (18.5%) | 8 (19.5%) | 7 (15.9%) | 7 (20.6%) | |||
| Unknown | 39 (32.8%) | 10 (24.4%) | 20 (45.5%) | 9 (26.5%) | |||
| LDH, U/L, median (IQR) | 181 [159–216] | 187 [162–208] | 178 [158–219] | 186 [150–217] | .812 | .815 | .876 |
| ICI | .790 | ||||||
| Camrelizumab | 23 (29.5%) | 11 (25.0%) | 12 (35.3%) | ||||
| Sintilimab | 24 (30.8%) | 15 (34.1%) | 9 (26.5%) | ||||
| Tislelizumab | 24 (30.8%) | 14 (31.8%) | 10 (29.4%) | ||||
| Toripalimab | 7 (8.97%) | 4 (9.09%) | 3 (8.82%) |
ICI = immune checkpoint inhibitor, IQR = interquartile range, LDH = lactate dehydrogenase, PD-L1 = programmed cell death ligand 1.
Table 2.
Clinical characteristics of patients after PSM.
| IC (N = 34) |
IAC (N = 34) |
P (IC vs IAC) | AC (N = 41) |
IC (N = 41) |
P (AC vs IC) | AC (N = 34) |
IAC (N = 34) |
P (AC vs IAC) | |
|---|---|---|---|---|---|---|---|---|---|
| Sex, n (%) | 1 | .586 | 1 | ||||||
| Male | 27 (79.4%) | 26 (76.5%) | 31 (75.6%) | 34 (82.9%) | 26 (76.5%) | 26 (76.5%) | |||
| Female | 7 (20.6%) | 8 (23.5%) | 10 (24.4%) | 7 (17.1%) | 8 (23.5%) | 8 (23.5%) | |||
| Age, yr, Median (IQR) |
65.5 [60–71] | 65.0 [60–69.8] | .735 | 62.0 [55–68] | 65.0 [60–71] | .097 | 63.0 [58–67.8] | 65.0 [60–69.8] | .272 |
| Smoking, n (%) | 1 | .244 | .615 | ||||||
| No | 11 (32.4%) | 11 (32.4%) | 17 (41.5%) | 11 (26.8%) | 14 (41.2%) | 11 (32.4%) | |||
| Yes | 23 (67.6%) | 23 (67.6%) | 24 (58.5%) | 30 (73.2%) | 20 (58.8%) | 23 (67.6%) | |||
| Bone metastasis, n (%) | .6 | .244 | .62 | ||||||
| No | 25 (73.5%) | 22 (64.7%) | 24 (58.5%) | 30 (73.2%) | 19 (55.9%) | 22 (64.7%) | |||
| Yes | 9 (26.5%) | 12 (35.3%) | 17 (41.5%) | 11 (26.8%) | 15 (44.1%) | 12 (35.3%) | |||
| Brain metastasis, n (%) | .054 | 1 | .105 | ||||||
| No | 29 (85.3%) | 21 (61.8%) | 35 (85.4%) | 36 (87.8%) | 28 (82.4%) | 21 (61.8%) | |||
| Yes | 5 (14.7%) | 13 (38.2%) | 6 (14.6%) | 5 (12.2%) | 6 (17.6%) | 13 (38.2%) | |||
| Liver metastasis, n (%) | 1 | .712 | 1 | ||||||
| No | 30 (88.2%) | 30 (88.2%) | 36 (87.8%) | 38 (92.7%) | 30 (88.2%) | 30 (88.2%) | |||
| Yes | 4 (11.8%) | 4 (11.8%) | 5 (12.2%) | 3 (7.32%) | 4 (11.8%) | 4 (11.8%) | |||
| Lung metastasis, n (%) | 1 | .375 | .627 | ||||||
| No | 19 (55.9%) | 18 (52.9%) | 20 (48.8%) | 25 (61.0%) | 15 (44.1%) | 18 (52.9%) | |||
| Yes | 15 (44.1%) | 16 (47.1%) | 21 (51.2%) | 16 (39.0%) | 19 (55.9%) | 16 (47.1%) | |||
| PD-L1 expression, n (%) | .531 | .051 | .097 | ||||||
| <1% | 10 (29.4%) | 14 (41.2%) | 12 (29.3%) | 11 (26.8%) | 10 (29.4%) | 14 (41.2%) | |||
| 1–49% | 6 (17.6%) | 4 (11.8%) | 4 (9.76%) | 8 (19.5%) | 4 (11.8%) | 4 (11.8%) | |||
| ≥50% | 11 (32.4%) | 7 (20.6%) | 3 (7.32%) | 10 (24.4%) | 2 (5.88%) | 7 (20.6%) | |||
| Unknown | 7 (20.6%) | 9 (26.5%) | 22 (53.7%) | 12 (29.3%) | 18 (52.9%) | 9 (26.5%) | |||
| TP53 mutation, n (%) | .147 | .11 | .125 | ||||||
| No | 18 (52.9%) | 12 (35.3%) | 25 (61.0%) | 17 (41.5%) | 19 (55.9%) | 12 (35.3%) | |||
| Yes | 6 (17.6%) | 13 (38.2%) | 6 (14.6%) | 5 (12.2%) | 6 (17.6%) | 13 (38.2%) | |||
| Unknown | 10 (29.4%) | 9 (26.5%) | 10 (24.4%) | 19 (46.3%) | 9 (26.5%) | 9 (26.5%) | |||
| KRAS mutation, n (%) | .96 | .103 | 1 | ||||||
| No | 17 (50.0%) | 18 (52.9%) | 23 (56.1%) | 15 (36.6%) | 18 (52.9%) | 18 (52.9%) | |||
| Yes | 7 (20.6%) | 7 (20.6%) | 8 (19.5%) | 7 (17.1%) | 7 (20.6%) | 7 (20.6%) | |||
| Unknown | 10 (29.4%) | 9 (26.5%) | 10 (24.4%) | 19 (46.3%) | 9 (26.5%) | 9 (26.5%) | |||
| LDH, U/L, median (IQR) |
180 [158–219] | 186 [150–217] | .936 | 187 [162–208] | 176 [158–219] | .799 | 192 [164–214] | 186 [150–217] | .481 |
IQR = interquartile range, LDH = lactate dehydrogenase, PD-L1 = programmed cell death ligand 1, PSM = propensity score matching..
3.2. Efficacy
Before PSM, 101 and 71 of 119 patients met the primary end-points of PFS and OS, respectively, with PFS and OS endpoint event rates of 84.9% and 59.7%, respectively, mPFS of 10.2 months (95% CI: 8.6–12.9) (Figure S1A, Supplemental Digital Content, https://links.lww.com/MD/Q652) and mOS of 30.1 months (95% CI: 26.1–34.4) (Figure S2A, Supplemental Digital Content, https://links.lww.com/MD/Q652). The PFS of the IAC group differed substantially from that of the AC group (mPFS: 15.75 [95% CI: 12.8–21.8] vs 8.3 months [95% CI: 7.8–10.4]; P = .0012) (Figure S1B, Supplemental Digital Content, https://links.lww.com/MD/Q652). The IAC group owned a numerically longer PFS than the IC group, but not statistically different (mPFS: 15.75 [95% CI: 12.8–21.8] vs 8.85 months [95% CI: 8.3–14.4]; P = .12) (Figure S1C, Supplemental Digital Content, https://links.lww.com/MD/Q652). The PFS of the IC group was not significantly different from that of the AC group (mPFS: 8.85 [95% CI: 8.3–14.4] vs 8.3 months [95% CI: 7.8–10.4]; P = .21) (Figure S1D, Supplemental Digital Content, https://links.lww.com/MD/Q652). The IAC group owned a better OS than the AC group (mOS: 35.9 [95% CI: 30.5 to NA] vs 26.2 months [95% CI: 22.5–32.6]; P = .016) (Figure S2B, Supplemental Digital Content, https://links.lww.com/MD/Q652). OS was numerically prolonged in the IAC group compared to that in the IC group, but not statistically different (mOS: 35.9 [95% CI: 30.5 to NA] vs 30.6 months [95% CI: 18.2 to NA]; P = .13) (Figure S2C, Supplemental Digital Content, https://links.lww.com/MD/Q652). The OS was not statistically different between the IC and AC groups (mOS: 30.6 [95% CI: 18.2 to NA] vs 26.2 months [95% CI: 22.5–32.6]; P = .49) (Figure S2D, Supplemental Digital Content, https://links.lww.com/MD/Q652). For 6- and 12-month PFS rates, the IAC group had significantly higher PFS rates than the AC and IC groups (IAC vs AC: [6-month: 100% vs 80.5%, P = .007; 12-month: 67.6% vs 26.8%, P = .001]; IAC vs IC: [6-month: 100% vs 81.8%, P = .008; 12-month: 67.6% vs 36.4%, P = .012]) (Figure S1B, S1C, Supplemental Digital Content, https://links.lww.com/MD/Q652); however, there was no difference between the IC and AC groups (6-month: 81.8% vs 80.5%, P = 1; 12-month: 36.4% vs 26.8%, P = .477) (Figure S1D, Supplemental Digital Content, https://links.lww.com/MD/Q652). For 12- and 36-month OS rates, the IAC group was numerically higher than the AC and IC groups, not statistically different (IAC vs AC: [12-month: 100% vs 92.7%, P = .246; 36-month: 20.6% vs 12.2%, P = .502]; IAC vs IC: [12-month: 100% vs 88.6%, P = .065; 36-month: 20.6% vs 9.09%, P = .195]) (Figure S2B, S2C, Supplemental Digital Content, https://links.lww.com/MD/Q652), and no difference between the IC and AC groups (12-month: 88.6% vs 92.7%, P = .714; 36-month: 9.09% vs 12.2%, P = .733) (Figure S2D, Supplemental Digital Content, https://links.lww.com/MD/Q652). Of the 119 patients, the optimal efficacy was PR in 75 patients, SD in 42 patients and PD in 2 patients with an ORR of 63%. The ORR were 53.7%, 76.5%, and 61.4% in the AC, IAC, and IC groups, respectively. The ORR in the IAC group was numerically better than that in the AC and IC groups, but not statistically different (Figure S1B, S1C, Supplemental Digital Content, https://links.lww.com/MD/Q652), nor was the ORR of the IC group different from that of the AC group (Figure S1D, Supplemental Digital Content, https://links.lww.com/MD/Q652).
After PSM, the PFS of the IAC group was better than that of the AC group (mPFS: 15.8 [95% CI: 12.8–21.8] vs 8.5 months [95% CI: 7.8–11.2]; P = .0057) (Fig. 2A). There was a numerically prolonged PFS in the IAC group compared to the IC group, but no statistical difference was observed (mPFS: 15.8 [95% CI: 12.8–21.8] vs 8.5 months [95% CI: 7.0–11.7]; P = .072) (Fig. 2B). The PFS in the IC group did not differ significantly from that in the AC group (mPFS: 8.6 [95% CI: 7.9–11.7] vs 8.3 months [95% CI: 7.8–10.4]; P = .43) (Fig. 2C). OS was longer in the IAC group than the AC group (mOS: 35.9 [95% CI: 30.5 to NA] vs 26.9 months [95% CI: 20.8–32.6]; P = .021) (Fig. 3A). The OS of the IAC group was numerically prolonged compared to that of the IC group, but not statistically different (mOS: 35.9 [95% CI: 30.5 to NA] vs 31.6 months [95% CI: 15.7 to NA]; P = .086) (Fig. 3B), and no significant difference in OS in the IC group compared to the AC group (mOS: 30.6 [95% CI: 18.2 to NA] vs 26.2 months [95% CI: 22.5–32.6]; P = .6) (Fig. 3C). In terms of PFS rates at 6 and 12 months, the IAC group owned significantly higher rates than the AC and IC groups (IAC vs AC: [6-month: 100% vs 82.4%, P = .025; 12-month: 67.6% vs 29.4%, P = .004]; IAC vs IC: [6-month: 100% vs 76.5%, P = .005; 12-month: 67.6% vs 29.4%, P = .004]) (Fig. 2A and B), but no statistically significant difference between the IC and AC groups (6-month: 80.5% vs 80.5%, P = 1; 12-month: 31.7% vs 26.8%, P = .808) (Fig. 2C). For 12- and 36-month OS rates, there were no statistical differences between the IAC and AC groups (12-month: 100% vs 91.2%, P = .239; 36-month: 20.6% vs 11.8%, P = .51) (Fig. 3A), between the IAC and IC groups (12-month: 100% vs 85.3%, P = .053; 36-month: 20.6% vs 8.82%, P = .304) (Fig. 3B), and between the IC and AC groups (12-month: 87.8% vs 92.7%, P = .712; 36-month: 9.76% vs 12.2%, P = 1) (Fig. 3C). In comparison to the AC group, the IAC group showed a numerical, but not statistically significant, improvement in ORR (76.5% vs 52.9%, P = .076) (Fig. 2A). No statistically significant difference in ORR was not observed between the IAC and IC groups (76.5% vs 58.8%, P = .195) (Fig. 2B), nor between the IC and AC groups (58.5% vs 53.7%, P = .824) (Fig. 2C).
Figure 2.
Kaplan–Meier analysis of progression-free survival (PFS) after propensity score matching (PSM). (A) Median PFS (mPFS), objective response rate (ORR), 6- and 12-month PFS rates in the IAC and AC groups; (B) mPFS, ORR, 6- and 12-month PFS rates in the IAC and IC groups; (C) mPFS, ORR, 6- and 12-month PFS rates in the IC and AC groups.
Figure 3.
Kaplan–Meier analysis of overall survival (OS) after propensity score matching (PSM). (A) Median OS (mOS), 12- and 36-month OS rates in the IAC and AC groups; (B) mOS, 12- and 36-month OS rates in the IAC and IC groups; (C) mOS, 12- and 36-month OS rates in the IC and AC groups.
3.3. Factors affecting PFS and OS
Thirteen variables, including age, sex, smoking, metastatic sites (bone, brain, liver, and lung), PD-L1 expression status, TP53 mutation status, KRAS mutation status, LDH, therapy, and efficacy to CR/PR, were subjected to univariate COX regression analysis. Those variables that had P < .2 in the univariate Cox analysis were included in the multivariate COX analysis.
3.3.1. Factors affecting PFS
Univariate COX analysis showed that age (HR = .975, P = .034), sex (HR = 1.576, P = .047), brain metastasis (HR = .579, P = .042), therapy (HR = .683, P = .0025), and optimal efficacy up to CR/PR (HR = .401, P < .0001) were factors affecting PFS. Multivariate COX analysis showed that age (HR = .975, P = .043), therapy (HR = .748, P = .029), and efficacy to CR/PR (HR = .447, P < .0005) were independent influences on PFS (Table 3).
Table 3.
COX regression analysis.
| PFS | OS | |||||||
|---|---|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | Univariate analysis | Multivariate analysis | |||||
| HR (95% CI) |
P value | HR (95% CI) |
P value | HR (95% CI) |
P value | HR (95% CI) |
P value | |
| Age (yr) | 0.975 (0.952–0.998) |
.034 | 0.975 (0.952–0.999) |
.043 | 0.981 (0.956–1.006) |
.133 | 0.976 (0.952–1) |
.051 |
| Sex (male/female) | 1.576 (1.006–2.47) |
.047 | 1.184 (0.741–1.891) |
.480 | 1.582 (0.933–2.683) | .089 | 1.705 (0.814–3.573) |
.157 |
| Smoking (no/yes) |
0.865 (0.575–1.302) |
.488 | 0.717 (0.443–1.159) |
.174 | 1.480 (0.758–2.891) |
.251 | ||
| Bone metastasis (no/yes) |
1.283 (0.854–1.929) |
.230 | 1.004 (0.615–1.638) |
.988 | ||||
| Brain metastasis (no/yes) |
0.579 (0.342–0.980) |
.042 | 0.766 (0.438–1.340) |
.350 | 0.673 (0.354–1.282) |
.229 | ||
| Liver metastasis (no/yes) |
0.857 (0.457–1.607) |
.631 | 0.804 (0.383–1.687) |
.564 | ||||
| Lung metastasis (no/yes) |
1.210 (0.817–1.794) |
.342 | 0.990 (0.613–1.582) |
.966 | ||||
| PD-L1 status (<1%/1–49%/ ≥50%/unknown) |
0.943 (0.800–1.111) |
.481 | 0.927 (0.765–1.122) |
.435 | ||||
| TP53 mutation (no/yes/unknown) |
0.935 (0.746–1.171) |
.556 | 1.099 (0.841–1.436) |
.491 | ||||
| KRAS mutation (no/yes/unknown) |
1.045 (0.843–1.295) |
.690 | 1.055 (0.808–1.379) |
.694 | ||||
| LDH, U/L | 0.999 (0.996–1.001) |
.287 | 1 (0.997–1.003) |
.859 | ||||
| Therapy (AC/IC/IAC) |
0.683 (0.534–0.874) |
.003 | 0.748 (0.576–0.970) |
.029 | 0.721 (0.540–0.962) |
.026 | 0.703 (0.545–0.907) |
.007 |
| Efficacy to CR/PR (no/yes) |
0.401 (0.265–0.606) |
.000 | 0.447 (0.291–0.689) |
.000 | 0.356 (0.216–0.584) |
.000 | 0.443 (0.288–0.681) |
.000 |
CI = confidence interval, CR = complete response, HR = hazard ratio, LDH = lactate dehydrogenase, OS = overall survival, PD-L1 = programmed cell death ligand 1, PFS = progression-free survival, PR = partial response.
3.3.2. Factors affecting OS
Univariate COX analysis showed that age (HR = .981, P = .133), sex (HR = 1.582, P = .089), smoking (HR = .717, P = .174), therapy (HR = .721, P = .026), and optimal efficacy up to CR/PR (HR = .356, P < .0001) were factors affecting OS. Multivariate COX analysis showed that therapy (HR = .703, P = .0066), and efficacy to CR/PR (HR = .443, P = .0002) were independent influences on OS (Table 3).
3.4. Subgroup analysis
Subgroup analyses were performed on 11 variables, including age, sex, smoking, metastatic sites (bone, brain, liver, and lung), PD-L1 expression status, TP53 mutation status, KRAS mutation status, and LDH.
3.4.1. Subgroup analysis of PFS
A subgroup analysis of IAC versus AC was performed, and 2 subgroups (sex and smoking) showed heterogeneity, indicating that the extent of PFS benefit from IAC appeared to be reduced in women (P = .013 for interaction) and patients with no smoking history (P = .015 for interaction) (Figure S3, Supplemental Digital Content, https://links.lww.com/MD/Q652). A subgroup analysis of IAC versus IC showed heterogeneity in the subgroups of bone metastasis (P = .002 for interaction) and TP53 mutation (P = .015 for interaction), suggesting that the extent of PFS benefit from IAC appeared to be increased in patients with bone metastasis (P = .017). Furthermore, it appeared that the extent of PFS benefit from IAC was increased in patients without TP53 mutation (P = .154) and the extent of PFS benefit from IC was increased in patients with TP53 mutation (P = .59), but the difference was not statistically significant (Figure S4, Supplemental Digital Content, https://links.lww.com/MD/Q652). A subgroup analysis of IC versus AC showed no heterogeneity in any of the subgroups (Figure S5, Supplemental Digital Content, https://links.lww.com/MD/Q652), indicating that a significant difference in the extent of PFS benefit was not found between the IC and AC groups in any subgroup.
3.4.2. Subgroup analysis of OS
Subgroup analysis of IAC versus AC showed no heterogeneity in any of the subgroups, suggesting that the OS benefit of IAC was superior to that of AC in any subgroup (Figure S6, Supplemental Digital Content, https://links.lww.com/MD/Q652). A subgroup analysis of IAC versus IC showed heterogeneity in the subgroups of age (P = .005 for interaction), KRAS mutation (P = .013 for interaction), and TP53 mutation (P = .005 for interaction), suggesting that IAC appeared to have a more pronounced OS benefit in patients aged > 65 years (Figure S7, Supplemental Digital Content, https://links.lww.com/MD/Q652). Subgroup analysis of IC versus AC showed no heterogeneity in any of the subgroups, indicating that OS benefit did not differ significantly between IC and AC in any subgroup (Figure S8, Supplemental Digital Content, https://links.lww.com/MD/Q652).
3.5. Safety
As shown in Table 4, 14 AEs were observed in 119 patients, including nausea, vomiting, fatigue, rash, mucositis, hypertension, hypothyroidism, proteinuria, fever, increased ALT/ AST, neutropenia, thrombocytopenia, pituitary inflammation, and reactive cutaneous capillary endothelial proliferation. No significant differences in AEs were observed among the 3 groups. Neutropenia was the most common AEs in the IAC, IC, and AC groups, with 8 (23.5%), 9 (20.5%), and 9 (22%) cases in grades 1 to 2, and 4 (11.8%), 2 (4.55%), and 2 (4.88%) cases in grades 3 to 4, respectively. Nausea and vomiting were also more common among the 3 groups. The frequency of hypertension was higher in the IAC and AC groups (14.7% and 14.6%, respectively). One case of immune-associated pituitary inflammation was observed in the IAC and IC groups, respectively. One case of reactive cutaneous capillary endothelial proliferation was observed in the IAC group.
Table 4.
Adverse events.
| All (N = 119) |
AC (N = 41) |
IC (N = 44) |
IAC (N = 34) |
P (All) |
P (AC vs IC) | P (AC vs IAC) | P (IC vs IAC) | |
|---|---|---|---|---|---|---|---|---|
| Nausea | .987 | 1 | 1 | 1 | ||||
| Grade1–2 | 27 (22.7%) | 9 (22.0%) | 10 (22.7%) | 8 (23.5%) | ||||
| Vomiting | 1 | 1 | 1 | 1 | ||||
| Grade1–2 | 16 (13.4%) | 5 (12.2%) | 6 (13.6%) | 5 (14.7%) | ||||
| Fatigue | 1 | 1 | 1 | 1 | ||||
| Grade1–2 | 17 (14.3%) | 6 (14.6%) | 6 (13.6%) | 5 (14.7%) | ||||
| Rash | .669 | .925 | .925 | 1 | ||||
| Grade1–2 | 6 (5.04%) | 1 (2.44%) | 3 (6.82%) | 2 (5.88%) | ||||
| Mucositis | 1 | 1 | 1 | 1 | ||||
| Grade1–2 | 3 (2.52%) | 1 (2.44%) | 1 (2.27%) | 1 (2.94%) | ||||
| Hypertension | .696 | .611 | 1 | .611 | ||||
| Grade1–2 | 15 (12.6%) | 6 (14.6%) | 4 (9.09%) | 5 (14.7%) | ||||
| Grade3–4 | 2 (1.68%) | 1 (2.44%) | 0 (0.00%) | 1 (2.94%) | ||||
| Hypothyroidism | .263 | .363 | .363 | 1 | ||||
| Grade1–2 | 5 (4.20%) | 0 (0.00%) | 3 (6.82%) | 2 (5.88%) | ||||
| Proteinuria | .53 | .724 | 1 | .724 | ||||
| Grade1–2 | 2 (1.68%) | 1 (2.44%) | 0 (0.00%) | 1 (2.94%) | ||||
| Fever | 1 | 1 | 1 | 1 | ||||
| Grade1–2 | 4 (3.36%) | 1 (2.44%) | 2 (4.55%) | 1 (2.94%) | ||||
| Increased ALT/AST | .771 | 1 | 1 | 1 | ||||
| Grade1–2 | 4 (3.36%) | 1 (2.44%) | 2 (4.55%) | 1 (2.94%) | ||||
| Grade3–4 | 1 (0.84%) | 0 (0.00%) | 0 (0.00%) | 1 (2.94%) | ||||
| Neutropenia | .735 | 1 | .835 | .835 | ||||
| Grade1–2 | 26 (21.8%) | 9 (22.0%) | 9 (20.5%) | 8 (23.5%) | ||||
| Grade3–4 | 8 (6.72%) | 2 (4.88%) | 2 (4.55%) | 4 (11.8%) | ||||
| Thrombocytopenia | .989 | 1 | 1 | 1 | ||||
| Grade1–2 | 12 (10.1%) | 4 (9.76%) | 4 (9.09%) | 4 (11.8%) | ||||
| Grade3–4 | 4 (3.36%) | 1 (2.44%) | 2 (4.55%) | 1 (2.94%) | ||||
| Pituitary inflammation | .743 | 1 | 1 | 1 | ||||
| Grade1–2 | 2 (1.68%) | 0 (0.00%) | 1 (2.27%) | 1 (2.94%) | ||||
| RCCEP | .286 | 1 | .453 | .453 | ||||
| Grade1–2 | 1 (0.84%) | 0 (0.00%) | 0 (0.00%) | 1 (2.94%) |
ALT = alanine transaminase, AST = aspartate aminotransferase, RCCEP = reactive cutaneous capillary endothelial proliferation.
4. Discussion
In this study, an analysis of 119 patients was conducted to evaluate the efficacy of 3 initial treatments (IAC, IC, and AC) for metastatic lung adenocarcinoma with driver gene negativity. The primary end-points were OS and PFS, and the secondary end-points were ORR, 6- and 12-month PFS rates, and 12- and 36-month OS rates. Owing to the unbalanced nature of clinical characteristics, PSM was used to match patients to control for confounders and selective bias.
Bevacizumab suppresses tumor growth by binding to and inhibiting the action of vascular endothelial growth factor. The results of 2 phase III clinical studies established bevacizumab as initial therapy for advanced non-squamous NSCLC. As demonstrated by Eastern Cooperative Oncology Group 4599, there was a significant benefit in OS and PFS from the combination of bevacizumab with chemotherapy compared with chemotherapy.[15] According to the AVAIL study, bevacizumab in conjunction with chemotherapy significantly increased the PFS.[15] Recent studies have indicated that PD-1 and PD-L1 inhibitors can significantly improve the prognosis of patients with metastatic NSCLC without driver gene mutations. A phase III clinical study confirmed that patients with driver-negative metastatic NSCLC with PD-L1 ≥ 50% who received pembrolizumab had significantly extended OS and PFS compared to those who received chemotherapy.[16] The results of KEYNOTE-189 demonstrated that chemotherapy in conjunction with pembrolizumab substantially prolonged OS and PFS in non-squamous NSCLC patients with driver gene negativity, regardless of PD-L1 status.[17] In IMpower150, atezolizumab added to combination chemotherapy with bevacizumab substantially improved PFS and OS for advanced non-squamous NSCLC patients with driver gene negativity, and in the atezolizumab combination chemotherapy group, OS improved numerically but not statistically significantly compared to the bevacizumab combination chemotherapy group.[11,12]
All 3 treatments, including IAC, IC, and AC, can be utilized as initial therapies for untreated advanced lung adenocarcinoma with driver gene negativity. In this study, we evaluated the efficacy of the 3 treatments, and the ICIs included camrelizumab, sintilimab, tislelizumab, and toripalimab. The efficacy of the 4 ICIs for metastatic non-squamous NSCLC has been demonstrated. Patients with advanced non-squamous NSCLC without mutations of EGFR or ALK, treated with camrelizumab coupled with chemotherapy, had a substantially longer OS (mOS: 27.1 vs 19.8 months; HR = .72 [95% CI: .57–.92]).[18] The ORIENT-11 study confirmed that sintilimab plus chemotherapy substantially improved OS in patients with advanced non-squamous NSCLC without EGFR and ALK mutations (mOS: 24.2 vs 16.8 months; HR = .65 [95% CI: .5–.85]).[19] RATIONALE 304 showed that a combination of chemotherapy and tislelizumab significantly extended PFS in advanced non-squamous NSCLC without mutations of EGFR and ALK compared to chemotherapy (mPFS: 9.7 vs 7.6 months; HR = .645 [95% CI: .462–.902]).[20] Based on the results of CHOICE-01, toripalimab coupled with chemotherapy substantially improved PFS in metastatic NSCLC patients without EGFR or ALK mutations compared to chemotherapy (mPFS: 8.4 months vs 5.6 months, HR = .49 [95% CI: .39–.61]).[21] In this study, the PFS and OS of the IAC group were substantially longer than those of the AC group, and the IAC group showed a numerical improvement in PFS and OS compared with the IC group, but no statistical difference was observed, and the PFS and OS benefit of the IC group were not substantially different from those of the AC group. Our findings suggested that IAC had a better prognostic advantage. In comparison to chemotherapy coupled with bevacizumab, nivolumab coupled with chemotherapy and bevacizumab improved PFS in a phase III trial involving untreated patients with stage IIIB/IV or recurrent non-squamous NSCLC (mPFS: 12.1 months vs 8.1 months; HR: .56; 96.4% CI: [.43–.71]; P < .0001).[22] In our study, in comparison to the AC group, the PFS of the IAC group was significantly longer, which is consistent with the above findings. Japanese researchers analyzed the difference in efficacy of atezolizumab coupled with carboplatin and pemetrexed (APP) and atezolizumab coupled with carboplatin, pemetrexed, and bevacizumab (APPB), the PFS of APPB was numerically better than that of APP in advanced non-squamous NSCLC patients with driver gene negativity, but not statistically significant (mPFS: 9.6 vs 7.7 months; HR:.86; 95% CI: [.7–1.07]; P = .92).[23] This result is consistent with our findings. The mPFS of the atezolizumab coupled with chemotherapy (ACP) group versus the BCP group in the Impower-150 trial was 6.8 and 6.3 months, respectively. The final OS analysis showed a numerical but not statistically significant prolongation of OS in the ACP group compared to that in the BCP group (mOS: 19.0 vs 14.7 months; HR: .84).[11,12] In this study, the PFS and OS in the IC group were numerically superior to those in the AC group, but the difference was not statistically significant, similar to the Impower 150 results.
In a retrospective study from China that compared the effectiveness of IC, AC, and IAC in PD-L1-negative metastatic lung adenocarcinoma patients with driver gene negativity, IAC showed significantly better PFS than AC and IC; however, the OS benefit was not significant, and there was no difference in OS and PFS benefit between AC and IC.[24] Two other retrospective studies, comparing the effectiveness of IC and AC in advanced non-squamous NSCLC patients with driver gene negativity showed a significantly prolonged PFS in the IC group compared with the AC group, but no difference in OS.[25,26] Our study showed that in terms of OS and PFS, the IAC group was significantly better than the AC group, the IAC group was numerically prolonged compared to the IC group but not statistically different, and no statistical difference between the IC and AC groups. Differences in results might be due to the fact that the above studies had different populations than those we enrolled. Our results indicate that the short- and long-term efficacy of IAC is significant.
To further explore the factors influencing PFS and OS, Cox analysis was conducted. COX analysis showed that different treatment regimens and whether CR or PR was achieved with optimal efficacy were factors affecting PFS and OS. Different treatment regimens were factors affecting PFS and OS, indicating significant differences in efficacy across treatment regimens. Whether the optimal efficacy achieved CR or PR was an independent influence on PFS, suggesting that patients who achieved CR or PR with treatment had a better prognosis. Previous studies have shown that malignant tumors in the elderly are relatively less malignant, progress relatively slowly, and have a relatively longer survival period.[27] This was consistent with our study, which showed that age was an independent influence on PFS.
Next, subgroup analysis was performed, and heterogeneity was found in some subgroups. The PFS benefit in the IAC group appeared to be reduced in female patients with no history of smoking compared to the AC group. The PFS benefit of IAC in patients with bone metastases appeared to be increased than that of IC. IAC appeared to have a more pronounced OS benefit in patients aged > 65 years. In our study, heterogeneity was found in some subgroups; however, due to the limited sample size, there was a possibility of error, and further clinical trials are needed to verify this.
We are well aware that there were some limitations to our study. First, the sample size was insufficient, which might result in certain errors. Second, among 119 patients, 43 had unknown PD-L1 expression, 39 had unknown TP53 and KRAS mutation status, and there was a lack of data on some immune-related indicators, such as tumor mutation burden and micro-satellite instability. Finally, since this was a retrospective study conducted at a single center, bias was inevitable.
5. Conclusion
In conclusion, our results suggested that for the initial therapy of metastatic lung adenocarcinoma patients with driver gene negativity, the survival benefit of IAC was significantly better than that of AC, the benefit of IAC was also numerically better than that of IC, but not statistically significant, and the benefit between IC and AC was not significantly different. In addition, no significant differences in AEs were observed among the 3 groups. Therefore, we concluded that IAC might be the best choice for the initial therapy of metastatic lung adenocarcinoma with driver gene negativity.
Author contributions
Conceptualization: Jingjing Cong.
Data curation: Anna Wang, Yingjia Wang.
Formal analysis: Junjian Pi.
Funding acquisition: Hongmei Li.
Methodology: Jingjing Cong.
Project administration: Hongmei Li.
Software: Yingjia Wang.
Supervision: Kaijing Liu, Hongmei Li.
Writing – original draft: Jingjing Cong, Anna Wang.
Writing – review & editing: Junjian Pi, Kaijing Liu.
Supplementary Material
Abbreviations:
- AEs
- adverse events
- ALK
- anaplastic lymphoma kinase
- CI
- confidence interval
- CR
- complete response
- EGFR
- epidermal growth factor receptor
- HR
- hazard ratio
- ICI
- immune checkpoint inhibitor
- LDH
- lactate dehydrogenase
- NSCLC
- non-small cell lung cancer
- ORR
- objective response rate
- OS
- overall survival
- PD
- progressive disease
- PD-1
- programmed cell death 1
- PD-L1
- programmed cell death ligand 1
- PFS
- progression-free survival
- PR
- partial response
- PSM
- propensity score matching
This research was supported by Qingdao Science and Technology Demonstration Special Project for the Benefit of the People (No. 21-1-4-rkjk-4-nsh).
Ethics committee of the Affiliated Hospital of Qingdao University examined and authorized our study (approval number: QYFYWZLL29230).
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Supplemental Digital Content is available for this article.
How to cite this article: Cong J, Wang A, Wang Y, Pi J, Liu K, Li H. Efficacy of PD-1 inhibitor plus chemotherapy and bevacizumab in initial therapy of metastatic non-squamous non-small cell lung cancer with driver gene negativity: A real-world retrospective study. Medicine 2025;104:47(e44157).
Contributor Information
Jingjing Cong, Email: 15908014650@163.com.
Anna Wang, Email: 18953285958@163.com.
Yingjia Wang, Email: 18953285958@163.com.
Junjian Pi, Email: platon_jian@163.com.
Kaijing Liu, Email: lkaijing555@163.com.
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