Comparative efficacy of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer: A network meta-analysis

Shuiyu Lin; Tingting Liu; Jun Chen; Guang Li; Jun Dang

doi:10.1371/journal.pone.0252751

. 2021 Jun 4;16(6):e0252751. doi: 10.1371/journal.pone.0252751

Comparative efficacy of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer: A network meta-analysis

Shuiyu Lin ¹, Tingting Liu ², Jun Chen ³, Guang Li ¹, Jun Dang ^1,^*

Editor: Ahmed Negida⁴

PMCID: PMC8177625 PMID: 34086780

Abstract

Background

It remains unclear which treatment is the most effective for previously treated patients with advanced esophageal and esophagogastric junction (EGJ) cancer. We conducted a network meta-analysis to address this important issue.

Methods

PubMed, Embase, Cochrane Library, and Web of Science databases were searched for relevant phase II and III randomized controlled trials (RCTs). Overall survival (OS) was the primary outcome of interest, which was reported as hazard ratio (HR) and 95% confidence intervals (CIs).

Results

Sixteen RCTs involving 3372 patients and evaluating 15 treatments were included in this network meta-analysis. Ramucirumab+chemotherapy (CT) (HR = 0.52, 95% CI: 0.35–0.77) and use of programmed death receptor 1 (PD-1) inhibitors, including camrelizumab (HR = 0.71, 95% CI: 0.57–0.88), sintilimab (HR = 0.70, 95% CI: 0.50–0.98), nivolumab (HR = 0.76, 95% CI: 0.62–0.94), and pembrolizumab (HR = 0.84, 95% CI: 0.72–0.98), conferred better OS than CT; however, this OS benefit was not observed for PD-L1 inhibitor (avelumab) and other target agents (trastuzumab, everolimus, gefitinib, and anlotinib). In subgroup analysis, ramucirumab+CT and pembrolizumab showed significant improvement in OS, when compared to CT, in esophageal/EGJ adenocarcinoma (AC) cases; moreover, all PD-1 inhibitors had significant OS advantage over CT in treating esophageal squamous cell carcinoma (SCC). Based on treatment ranking in terms of OS, ramucirumab+CT and camrelizumab were ranked the best treatments for patients with AC and SCC, respectively.

Conclusions

Ramucirumab+CT and PD-1 inhibitors were superior to CT for previously treated cases of advanced esophageal/EGJ cancer. Ramucirumab+CT seemed to be the most effective treatment in patients with esophageal/EGJ AC, while use of PD-1 inhibitors, especially camrelizumab, was likely to be the optimal treatment in patients with esophageal SCC.

Introduction

Esophageal cancer is characterized as an aggressive disease, and almost 50% of patients with esophageal cancer are diagnosed at an advanced stage [1]. Esophageal cancer has two main histological subtypes: esophageal adenocarcinoma (AC) and esophageal squamous cell carcinoma (SCC). Esophageal SCC is more prevalent in the upper and middle third of the esophagus, while AC usually arises from the distal third of the esophagus or the esophagogastric junction (EGJ). Systemic chemotherapy (CT) plays an essential role in the treatment of patients with advanced disease, in whom the median survival is only around 1 year [2]. In the attempts to improve the survival of this population, researchers have been investigating the efficacy of various target agents for a decade, such as those targeting epidermal growth factor receptor (EGFR) [3], vascular endothelial growth factor receptor two (VEGFR2) [4, 5], tyrosine kinase [6], HER2 gene [7, 8], and the mechanistic target of rapamycin (mTOR) pathway [9]. These agents have shown different degrees of efficacy outcomes.

More recently, there has been increased interest in immune checkpoint inhibitors (ICIs) for the treatment of advanced esophageal cancer [10–17]. Several phase III trials [12, 13, 15, 16] have demonstrated that, compared with CT, inhibitors of programmed death receptor 1 (PD-1) and its ligand, PD-L1, were associated with significant longer overall survival (OS) and a manageable safety profile in previously treated patients with advanced esophageal cancer.

Due to the lack of head-to-head comparison trials, it remains unclear whether ICIs have superior efficacies over targeted therapies; furthermore, the optimal regimen for previously treated patients with advanced esophageal/EGJ cancer remains controversial. Thus, we performed a network meta-analysis to assess the comparative efficacy and safety of different treatments, attempting to identify the most effective treatment for this patient population.

Methods

Literature search strategy

We conducted this network meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (S1 Table) [18]. We systematically searched PubMed, Embase, Cochrane Library, Web of Science databases, and the recent congresses of American Society of Clinical Oncology and European Society for Medical Oncology for available studies before July 1, 2020. The search strategy is detailed in S2 Table. Manual searching of reference lists of the relevant publications were also performed.

Inclusion and exclusion criteria

Studies were included if they met all of the following criteria: (1) phase II and III randomized controlled trials (RCTs) in recurrent or metastatic esophageal/EGJ cancer patients whose disease has progressed during or after previous systemic treatment; (2) compared ICIs or targeted therapies with CT, best supportive care (BSC), or placebo; (3) reported at least one of the following outcome data in each arm: OS, progression-free survival (PFS), objective response rate (ORR), and serious adverse events (SAEs); and (4) published in English. RCTs enrolling patients with both esophageal/EGJ cancer and gastric cancer were also included if they described the results for esophageal/EGJ cancer separately.

Data extraction

Two investigators independently extracted the following information from each trial: first author or title of the RCT, study design, region, histological type, location, follow-up time, number of patients, interventions, hazard ratios (HRs) and their 95% confidence intervals (CIs) of PFS and OS, and odds ratios (ORs) and their 95% CIs of ORR and SAEs.

Quality assessment

Two investigators independently assessed the risk of bias of each study using Cochrane Collaboration’s tool [19], which includes the following five domains: sequence generation, allocation concealment, blinding, incomplete data, and selective reporting. A RCT was finally classified to have “low risk of bias” (all domains indicated as low risk), “high risk of bias” (one or more domains indicated as high risk), or “unclear risk of bias” (more than three domains indicated as unclear risk).

Statistical analysis

The statistical analyses were performed by two investigators (SL and TL). The primary outcome was OS, while the secondary outcomes included PFS, ORR, and SAEs. HRs or ORs and their 95% CIs were used as summary statistics. For direct comparisons, standard pairwise meta-analysis was conducted using the Review Manager 5.3 (Cochrane Collaboration, Oxford, UK). Heterogeneity was assessed using chi-square (χ²) and I-square (I²) tests. A random-effects model was used for data with P-value over 0.10 or I² over 50%, which indicated substantial heterogeneity; otherwise, a fixed-effects model was used.

Bayesian network meta-analyses were performed using a Markov Chain Monte Carlo simulation technique in JAGS and GeMTC package in R (https://drugis.org/software/r-packages/gemtc). As most direct evidence came from one trial, the fixed-effects consistency model was employed [20]. For each outcome measure, three Markov chains were generated automatically and run simultaneously. For each chain, 150000 sample iterations were generated with 100 000 burn-ins and a thinning interval of 10. The convergence of the model was assessed using the traces plot and Brooks-Gelman-Rubin method [21]. Surface under the cumulative ranking curve (SUCRA) method [22] was used to assess relative efficiency and safety rankings. A SUCRA of one indicates that the treatment is certain to be the best and zero if the treatment is certain to be the worst. The transitivity assumption was evaluated by comparing the distribution of potential effect modifiers (sample size, median age, and median follow-up time) across treatment comparisons [23]. Global inconsistency was assessed by comparing the fit of consistency and inconsistency models using deviance information criteria [24, 25]. Node-splitting analysis was used to assess whether there was inconsistency between direct and indirect results within the treatment loop [26], with P<0.05 indicating significant inconsistency. Sensitivity analyses were conducted to evaluate the stability of results, omitting trials with sample size of less than 50, or trials of phase II and phase II/III. In addition, we performed subgroup analyses according to histologic type. Publication bias was examined using funnel plots [27].

Results

Literature search results and characteristics of included RCTs

We identified 1895 records from the initial literature search and retrieved and reviewed 143 potentially eligible reports in full text (Fig 1). The relevant references were also reviewed for missed studies. Finally, 16 RCTs [3–17, 28, 29] were deemed eligible for inclusion with a total of 3372 patients enrolled to receive 15 different treatments, including PD-1/L1 inhibitors (avelumab, camrelizumab, nivolumab, pembrolizumab, and sintilimab), target agents (anlotinib, everolimus, gefitinib, ramucirumab, ramucirumab+CT, trastuzumab, trastuzumab deruxtecan [T-DXd]), CT, BSC, and placebo. The baseline characteristics of the included trials are shown in Table 1. All studies were multinational trials, and a total of 12 studies (75%) were phase III trials. The median sample size was 145 participants (range, 24–628). The median age was 62 years (range, 59.1–65.5 years). The median follow-up time was 10.0 months (range, 6.7–20.7 months).

Table 1. Characteristics of included trials.

Trial	Design	Time	Region	Primary	Treatment	Sample	Meadian	Median	Histologic
		Range		Endpoint	Details	Size	Age	Follow-up	type
							(years)	(months)
COG/2014 [3]	III	2009–2011	multicentre	OS	Gefitinib	224	64.7	NR	SCC+AC
					BSC/Placebo	225	64.9
RAINBOW/2014 [4]	III	2010–2012	multicentre	OS	Ramucirumab+CT	66	61	7.9	AC
					CT	71	61
REGARD/2014 [5]	III	2009–2012	multicentre	OS	Ramucirumab	59	60	NR	AC
					BSC/Placebo	32	60
ALTER1102/2019 [6]	II	2016–2018	multicentre	PFS	Anlotinib	109	60.6	NR	SCC
			(China)		BSC/Placebo	55	60.7
GATSBY/2017 [7]	II/III	2012–2013	multicentre	OS	Trastuzumab	77	62	17.5	AC
					CT	33	62	15.4
DESTINY-Gastric01/2020 [8]	II	2017–2019	multicentre	ORR	T-DXd	16	65	NR	AC
					CT	8	66
GRANITE-1/2013 [9]	III	2009–2010	multicentre	OS	Everolimus	118	62	14.3	AC
					BSC/Placebo	69	62
ATTRACTION-2/2017 [10]	III	2014–2016	multicentre	OS	Nivolumab	30	62	8.87	AC
			(Asia)		BSC/Placebo	12	61	8.59
Gastric 300/2018 [11]	III	2015–2017	multicentre	OS	Avelumab	63	59	10.6	AC
					CT	48	61
KEYNOTE-061/2018 [12, 13]	III	2015–2016	multicentre	OS/PFS	Pembrolizumab	62	64	7.9	AC
					CT	73	62
KEYNOTE-181/2019 [14]	III	NR	multicentre	OS	Pembrolizumab	314	63	20.8	SCC+AC
					CT	314	62	20.6
Attraction-3/2019 [15]	III	2016–2017	multicentre	OS	Nivolumab	210	64	10.5	SCC
			(Asia)		CT	209	67	8.0
ESCORT/2019 [16]	III	2017–2018	multicentre	OS	Camrelizumab	228	60	8.3	SCC
			(China)		CT	220	60	6.2
ORIENT-2/2020 [17]	II	2017–2018	multicentre	OS	Sintilimab	95	58.8	7.2	SCC
					CT	95	59.4	6.2
COUGAR-02/2014 [28]	III	2008–2012	multicentre	OS	CT	45	65	12	AC
					BSC/Placebo	47	66
TAGS/2018 [29]	III	2016–2018	multicentre	OS	CT	98	64	10.7	AC
					BSC/Placebo	47	63

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Abbreviations: OS, overall survival; PFS, progression-free survival; ORR, objective response rate; AC, adenocarcinoma; SCC, squamous cell carcinoma; T-DXd, Trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care; NR, not reported.

Assessment of included trial

The risk of bias for included RCTs was summarized in S1 Fig. Overall, the risk of bias across studies was relatively low, with No RCTs rated with high risk of bias. Funnel plot analysis did not indicate any evident risk of publication bias for OS and PFS (S2 Fig).

Conventional pairwise meta-analysis

Results of pairwise meta-analysis and individual RCTs are shown in Table 2. There were two pairwise meta-analyses for OS, including CT vs BSC or placebo and pembrolizumab vs CT. CT significantly improved OS (HR = 0.69, 95% CI: 0.51–0.92; I² = 0%) when compared with BSC or placebo. No significant difference in OS was observed between pembrolizumab and CT (HR = 0.77, 95% CI: 0.54–1.10; I² = 67%).

Table 2. Results of single trial and direct comparison meta-analysis.

Treatment	Study	OS	PFS	ORR	SAEs	Heterogeneity I² (OS)
Treatment	Study	HR(95%CI)	HR(95%CI)	OR(95%CI)	OR(95%CI)	Heterogeneity I² (OS)
Pembrolizumab vs CT	[12, 13]	0.77(0.54–1.10)	0.82(0.66–1.02)	4.22(1.73–10.32)	0.32(0.22–0.46)	67%
CT vs BSC/Placebo	[28, 29]	0.69(0.51–0.92)	0.60(0.41–0.88)	NR	NR	0%
Gefitinib vs BSC/Placebo	[3]	0.90(0.74–1.09)	0.80(0.66–0.96)	6.17(0.74–51.63)	NR
Ramucirumab +CT vs CT	[4]	0.52(0.35–0.78)	0.39(0.26–0.59)	NR	NR
Ramucirumab vs BSC/Placebo	[5]	0.76(0.47–1.21)	0.39(0.23–0.65)	NR	NR
Anlotinib vs BSC/Placebo	[6]	1.18(0.79–1.75)	0.46(0.32–0.66)	2.12(0.43–10.34)	NR
Trastuzumab vs CT	[7]	1.18(0.70–2.01)	NR	NR	NR
Everolimus vs BSC/Placebo	[9]	0.84(0.61–1.16)	NR	NR	NR
Nivolumab vs BSC/Placebo	[10]	0.44(0.20–0.97)	NR	NR	NR
Avelumab vs CT	[11]	0.86(0.56–1.33)	1.22(0.78–1.91)	1.54(0.14–17.51)	NR
Nivolumab vs CT	[14]	0.77(0.62–0.96)	1.08(0.87–1.34)	0.87(0.51–1.49)	0.13(0.08–0.20)
Camrelizumab vs CT	[15]	0.71(0.57–0.87)	0.69(0.56–0.86)	3.72(1.98–6.99)	0.37(0.24–0.56)
Sintilimab vs CT	[17]	0.70(0.50–0.97)	1.00(0.77–1.39)	2.14(0.77–5.97)	0.39(0.20–0.77)
T-DXd vs CT	[8]	0.68(0.21–2.15)	NR	9.00(0.85–94.90)	NR

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Abbreviations: OS, overall survival; PFS, progression-free survival; ORR, objective response rate; SAEs, serious adverse events; HR, hazard ratio; CI, confidence interval; OR, odds ratio; T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care; NR, not reported.

Network meta-analysis

Fig 2 shows the network of eligible comparisons for OS and PFS. Network meta-analysis included all treatments for OS, 12 treatments for PFS, 7 treatments for ORR, and 5 treatments for SAEs. Results of the network meta-analysis are presented in Table 3. In terms of OS (Table 3A), ramucirumab+CT, camrelizumab, sintilimab, nivolumab, and pembrolizumab were more effective than CT (HR = 0.52, 95% CI: 0.35–0.77; HR = 0.71, 95% CI: 0.57–0.88; HR = 0.70, 95% CI: 0.50–0.98; HR = 0.76, 95% CI: 0.62–0.94; and HR = 0.84, 95% CI: 0.72–0.98), gefitinib (HR = 0.39, 95% CI: 0.23–0.66; HR = 0.53, 95% CI: 0.36–0.79; HR = 0.52, 95% CI: 0.33–0.84; HR = 0.57, 95% CI: 0.39–0.84; and HR = 0.63, 95% CI: 0.43–0.91), anlotinib (HR = 0.30, 95% CI: 0.16–0.55; HR = 0.40, 95% CI: 0.24–0.68; HR = 0.40, 95% CI: 0.22–0.72; HR = 0.43, 95% CI: 0.26–0.73; and HR = 0.48, 95% CI: 0.29–0.80); ramucirumab+CT, camrelizumab, sintilimab, and nivolumab were also more effective than everolimus (HR = 0.42, 95% CI: 0.23–0.75; HR = 0.57, 95% CI: 0.35–0.91; HR = 0.56, 95% CI: 0.33–0.96; and HR = 0.61, 95% CI: 0.38–0.97); ramucirumab+CT was also more effective than pembrolizumab (HR = 0.62, 95% CI: 0.40–0.95), ramucirumab (HR = 0.46, 95% CI: 0.23–0.91), and trastuzumab (HR = 0.44, 95% CI: 0.23–0.86).

Table 3. Results of network meta-analysis.

a. HR with 95%CI for OS

Ramucirumab+CT

0.73(0.47–1.15)

Camrelizumab

0.74(0.45–1.25)

1.01(0.69–1.50)

Sintilimab

0.68(0.44–1.07)

0.93(0.69–1.25)

0.92(0.62–1.37)

Nivolumab

0.76(0.22–2.59)

1.04(0.32–3.36)

1.03(0.31–3.41)

1.12(0.34–3.58)

T-DXd

0.62(0.40–0.95)

0.84(0.65–1.09)

0.83(0.58–1.20)

0.90(0.69–1.18)

0.81(0.25–2.61)

Pembrolizumab

0.61(0.34–1.11)

0.83(0.51–1.34)

0.82(0.47–1.41)

0.89(0.55–1.45)

0.80(0.23–2.75)

0.98(0.62–1.56)

Avelumab

0.52(0.35–0.77)

0.71(0.57–0.88)

0.70(0.50–0.98)

0.76(0.62–0.94)

0.68(0.22–2.18)

0.84(0.72–0.98)

0.86(0.55–1.32)

0.46(0.23–0.91)

0.63(0.35–1.13)

0.62(0.33–1.17)

0.67(0.38–1.20)

0.60(0.17–2.20)

0.75(0.42–1.32)

0.76(0.38–1.51)

0.89(0.51–1.53)

Ramucirumab

0.44(0.23–0.86)

0.60(0.34–1.06)

0.59(0.32–1.11)

0.65(0.36–1.13)

0.58(0.16–2.07)

0.71(0.41–1.23)

0.73(0.37–1.43)

0.85(0.50–1.43)

0.95(0.45–2.06)

Trastuzumab

0.42(0.23–0.75)

0.57(0.35–0.91)

0.56(0.33–0.96)

0.61(0.38–0.97)

0.55(0.16–1.88)

0.67(0.43–1.06)

0.69(0.37–1.26)

0.80(0.52–1.23)

0.90(0.51–1.61)

0.94(0.48–1.87)

Everolimus

0.39(0.23–0.66)

0.53(0.36–0.79)

0.52(0.33–0.84)

0.57(0.39–0.84)

0.51(0.15–1.74)

0.63(0.43–0.91)

0.64(0.37–1.11)

0.75(0.53–1.05)

0.84(0.51–1.40)

0.88(0.47–1.66)

0.94(0.64–1.36)

Gefitinib

0.35(0.22–0.57)

0.48(0.34–0.68)

0.47(0.31–0.73)

0.51(0.37–0.72)

0.46(0.14–1.52)

0.57(0.41–0.78)

0.58(0.34–0.97)

0.67(0.51–0.89)

0.76(0.47–1.22)

0.79(0.44–1.45)

0.84(0.61–1.16)

0.90(0.74–1.09)

Placebo/BSC

0.30(0.16–0.55)

0.40(0.24–0.68)

0.40(0.22–0.72)

0.43(0.26–0.73)

0.39(0.11–1.37)

0.48(0.29–0.80)

0.49(0.26–0.94)

0.57(0.35–0.92)

0.64(0.35–1.19)

0.67(0.33–1.38)

0.71(0.43–1.18)

0.76(0.49–1.18)

0.85(0.57–1.25)

Anlotinib

b. HR with 95%CI for PFS

Ramucirumab+CT

0.56(0.35–0.89)

Camrelizumab

0.60(0.28–1.29)

1.06(0.54–2.10)

Ramucirumab

0.51(0.26–0.99)

0.90(0.51–1.60)

0.85(0.45–1.60)

Anlotinib

0.47(0.30–0.75)

0.84(0.62–1.14)

0.79(0.40–1.56)

0.94(0.53–1.64)

Pembrolizumab

0.39(0.26–0.59)

0.69(0.56–0.86)

0.65(0.34–1.23)

0.77(0.45–1.29)

0.82(0.66–1.02)

0.39(0.23–0.65)

0.69(0.48–0.99)

0.65(0.32–1.31)

0.77(0.42–1.40)

0.82(0.57–1.18)

1.00(0.74–1.34)

Sintilimab

0.36(0.23–0.57)

0.64(0.47–0.87)

0.60(0.31–1.18)

0.71(0.40–1.25)

0.76(0.56–1.03)

0.93(0.75–1.15)

0.93(0.64–1.33)

Nivolumab

0.32(0.17–0.59)

0.57(0.35–0.93)

0.54(0.24–1.17)

0.63(0.32–1.25)

0.67(0.41–1.11)

0.82(0.53–1.29)

0.82(0.48–1.40)

0.88(0.54–1.46)

Avelumab

0.29(0.16–0.53)

0.52(0.32–0.83)

0.49(0.28–0.85)

0.58(0.38–0.86)

0.61(0.38–0.99)

0.75(0.49–1.14)

0.75(0.45–1.25)

0.81(0.50–1.30)

0.91(0.49–1.69)

Gefitinib

0.23(0.13–0.41)

0.41(0.27–0.64)

0.39(0.23–0.66)

0.46(0.32–0.66)

0.49(0.32–0.76)

0.60(0.41–0.88)

0.60(0.37–0.97)

0.65(0.42–1.00)

0.73(0.41–1.32)

0.80(0.66–0.96)

Placebo/BSC

c. OR with 95%CI for ORR

T-DXd

2.94(0.25–97.83)

Pembrolizumab

3.39(0.33–107.26)

1.16(0.39–3.64)

Camrelizumab

5.86(0.48–198.98)

1.99(0.48–7.97)

1.72(0.48–5.72)

Sintilimab

7.22(0.13–479.39)

2.41(0.07–37.83)

2.09(0.07–29.27)

1.22(0.03–19.61)

Avelumab

12.76(1.36–387.1)

4.38(1.85–11.66)

3.79(2.06–7.34)

2.21(0.81–6.77)

1.82(0.14–54.93)

14.83(1.49–461.57)

5.04(1.83–15.32)

4.36(1.94–10.17)

2.54(0.82–8.87)

2.09(0.15–66.03)

1.15(0.67–1.98)

Nivolumab

d. OR with 95%CI for SAEs

Nivolumab

0.40(0.22–0.72)

Pembrolizumab

0.36(0.19–0.66)

0.88(0.50–1.55)

Camrelizumab

0.33(0.15–0.74)

0.82(0.39–1.76)

0.93(0.42–2.08)

Sintilimab

0.13(0.08–0.20)

0.32(0.22–0.46)

0.36(0.24–0.55)

0.39(0.20–0.75)

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Abbreviations: HR, hazard ratios; OR, odds ratio; CI, confidence interval; OS, overall survival; PFS, progression-free survival; ORR, objective response rate; SAEs, serious adverse events; T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

With regard to PFS (Table 3B), ramucirumab+CT showed significant advantage over all PD-1/L1 inhibitors, including camrelizumab (HR = 0.56, 95% CI: 0.35–0.89), pembrolizumab (HR = 0.47, 95% CI: 0.30–0.75), sintilimab (HR = 0.39, 95% CI: 0.23–0.65), nivolumab (HR = 0.36, 95% CI: 0.23–0.57), and avelumab (HR = 0.32, 95% CI: 0.17–0.59); ramucirumab+CT was also more effective than other targeted therapies (except ramucirumab) and CT. Camrelizumab showed significant advantage over other PD-1/L1 inhibitors, including sintilimab (HR = 0.69, 95% CI: 0.48–0.99), nivolumab (HR = 0.64, 95% CI: 0.47–0.87), and avelumab (HR = 0.57, 95% CI: 0.35–0.93), except pembrolizumab; camrelizumab was also superior to CT and gefitinib.

Regarding ORR (Table 3C), T-DXd, pembrolizumab, and camrelizumab were better than CT (OR = 12.76, 95% CI: 1.36–387.1; OR = 4.38, 95% CI: 1.85–11.66; and OR = 3.79, 95% CI: 2.06–7.34) and nivolumab (OR = 14.83, 95% CI: 1.49–461.57; OR = 5.04, 95% CI: 1.83–15.32; and OR = 4.36, 95% CI: 1.94–10.17).

In terms of SAEs (Table 3D), nivolumab was safer than pembrolizumab (OR = 0.40, 95% CI: 0.22–0.72), camrelizumab (OR = 0.36, 95% CI: 0.19–0.66), and sintilimab (OR = 0.33, 95% CI: 0.15–0.74). All PD-1 inhibitors were safer than CT. Since most of the data for treatments with target agents were extracted from esophageal/EGJ cancer subgroups of studies involving participants with both esophageal/EGJ cancer and gastric cancer in which safety profiles were not reported, we failed to obtain enough data for their SAEs. Thus, comparative safety comparisons between target agents, PD-1/L1 inhibitors, and CT could not be performed.

Results of the treatment ranking based on SUCRA are presented in Table 4, with ranking curves shown in S3 Fig. In terms of OS, ramucirumab+CT was ranked the most effective treatment (0.95), followed by camrelizumab (0.79), sintilimab (0.79), nivolumab (0.72), and T-DXd (0.70). With regard to PFS, ramucirumab+CT (0.99) and camrelizumab (0.79) were ranked the best and the second-best treatments, respectively, followed by ramucirumab (0.78), anlotinib (0.67), and pembrolizumab (0.65). As for ORR, T-DXd (0.89) was ranked the best treatment, followed by pembrolizumab (0.73), camrelizumab (0.68), sintilimab (0.48), and avelumab (0.43). In terms of SAEs, nivolumab (1.00) was the least toxic treatment, followed by pembrolizumab (0.59), camrelizumab (0.47), sintilimab (0.43), and CT (0.00).

Table 4. Treatment ranking.

OS		PFS		ORR		SAEs		OS (AC)		OS (SCC)		PFS (AC)		PFS (SCC)
Treatment	SUCRA	Treatment	SUCRA	Treatment	SUCRA	Treatment	SUCRA	Treatment	SUCRA	Treatment	SUCRA	Treatment	SUCRA	Treatment	SUCRA
Ramucirumab+CT	0.95	Ramucirumab+CT	0.99	T-DXd	0.89	Nivolumab	1.00	Ramucirumab+CT	0.89	Camrelizumab	0.73	Ramucirumab+CT	0.98	Camrelizumab	0.94
Camrelizumab	0.79	Camrelizumab	0.79	Pembrolizumab	0.73	Pembrolizumab	0.59	Pembrolizumab	0.78	Sintilimab	0.73	Ramucirumab	0.79	Pembrolizumab	0.76
Sintilimab	0.79	Ramucirumab	0.78	Camrelizumab	0.68	Camrelizumab	0.47	Nivolumab	0.74	Nivolumab	0.53	CT	0.56	Sintilimab	0.32
Nivolumab	0.72	Anlotinib	0.67	Sintilimab	0.48	Sintilimab	0.43	T-DXd	0.66	Pembrolizumab	0.50	Avelumab	0.35	CT	0.32
T-DXd	0.70	Pembrolizumab	0.65	Avelumab	0.43	CT	0.00	Avelumab	0.56	CT	0.01	Gefitinib	0.29	Nivolumab	0.15
Pembrolizumab	0.62	CT	0.43	CT	0.18			CT	0.43			Placebo/BSC	0.04
Avelumab	0.60	Sintilimab	0.42	Nivolumab	0.11			Ramucirumab	0.34
CT	0.44	Nivolumab	0.33					Trastuzumab	0.28
Ramucirumab	0.38	Avelumab	0.24					Everolimus	0.25
Trastuzumab	0.33	Gefitinib	0.18
Everolimus Gefitinib	0.29	Placebo/BSC	0.02
Everolimus Gefitinib	0.23
Placebo/BSC	0.12
Anlotinib	0.06

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Abbreviations: SUCRA, surface under the cumulative ranking; OS, overall survival; PFS, progression-free survival; ORR, objective response rate; SAEs, serious adverse events; AC, adenocarcinoma; SCC, squamous cell carcinoma; T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

Transitivity, inconsistency, and sensitivity analysis

Assessment of transitivity indicated that the sample size, median age, and median follow-up time across treatments were relatively similar (S4 Fig). The fit of the consistency model was similar to that of the inconsistency model regarding all outcomes (S3 Table). There was one independent closed loop in the network for OS: nivolumab-CT-BSC/placebo. Analysis of inconsistency in OS showed that the indirect results were similar to the direct results (S5 Fig).

Sensitivity analysis omitting sample size less than 50 [8, 10], or phase II and phase II/III trials [6–8, 17] that did not affect the main results for OS (S4 Table).

Subgroup analysis

In the subgroup analysis of esophageal/EGJ AC (11 trials with 1102 patients receiving 10 treatments) (Table 5A), ramucirumab+CT showed significant OS advantage over CT (HR = 0.52, 95% CI: 0.35–0.77), ramucirumab (HR = 0.47, 95% CI: 0.24–0.94), trastuzumab (HR = 0.44, 95% CI: 0.23–0.86), and everolimus (HR = 0.43, 95% CI: 0.24–0.77); pembrolizumab significantly improved OS when compared to CT (HR = 0.64, 95% CI: 0.45–0.91) and everolimus (HR = 0.52, 95% CI: 0.30–0.92). In terms of PFS, ramucirumab+CT was more effective than CT (HR = 0.39, 95% CI: 0.26–0.59), avelumab (HR = 0.32, 95% CI: 0.17–0.59), gefitinib (HR = 0.29, 95% CI: 0.16–0.53); ramucirumab was superior to gefitinib (HR = 0.48, 95% CI: 0.27–0.84). Based on treatment ranking (Table 4 and S3 Fig), ramucirumab+CT was ranked the most effective treatment (0.89) in terms of OS, followed by pembrolizumab (0.78) and nivolumab (0.74); ramucirumab+CT (0.98) was still the best treatment in terms of PFS, followed by ramucirumab (0.79) and CT (0.56).

Table 5. Indirect results of subgroup analysis according to histological type.

a. AC
HR with 95%CI for OS
Ramucirumab+CT
0.81(0.48–1.38)	Pembrolizumab
0.81(0.32–2.09)	1.00(0.40–2.51)	Nivolumab
0.76(0.22–2.60)	0.94(0.28–3.20)	0.93(0.22–3.96)	T-DXd
0.61(0.34–1.08)	0.75(0.43–1.30)	0.74(0.29–1.90)	0.79(0.23–2.72)	Aelumab
0.52(0.35–0.77)	0.64(0.45–0.91)	0.64(0.27–1.49)	0.68(0.21–2.19)	0.86(0.56–1.32)	CT
0.47(0.24–0.94)	0.58(0.30–1.12)	0.58(0.23–1.45)	0.61(0.17–2.25)	0.78(0.38–1.58)	0.90(0.52–1.58)	Ramucirumab
0.44(0.23–0.86)	0.54(0.28–1.03)	0.54(0.20–1.48)	0.58(0.16–2.11)	0.73(0.37–1.43)	0.85(0.50–1.44)	0.94(0.43–2.03)	Trastuzumab
0.43(0.24–0.77)	0.52(0.30–0.92)	0.52(0.22–1.22)	0.56(0.16–1.95)	0.70(0.38–1.30)	0.82(0.53–1.27)	0.91(0.51–1.60)	0.97(0.49–1.93)	Everolimus
0.36(0.22–0.59)	0.44(0.28–0.70)	0.44(0.20–0.96)	0.47(0.14–1.56)	0.59(0.35–1.00)	0.69(0.51–0.92)	0.76(0.47–1.22)	0.81(0.44–1.45)	0.84(0.61–1.15)	Placebo/BSC
HR with 95%CI for PFS
Ramucirumab+CT
0.60(0.28–1.29)	Ramucirumab
0.39(0.26–0.59)	0.65(0.34–1.24)	CT
0.32(0.17–0.59)	0.53(0.24–1.17)	0.82(0.52–1.29)	Avelumab
0.29(0.16–0.53)	0.48(0.27–0.84)	0.74(0.48–1.15)	0.90(0.48–1.70)	Gefitinib
0.23(0.13–0.41)	0.39(0.23–0.66)	0.60(0.41–0.88)	0.73(0.40–1.32)	0.81(0.65–1.01)	Placebo/BSC
b.SCC
HR with 95%CI for OS
Camrelizumab
1.01(0.68–1.50)	Sintilimab
0.92(0.68–1.24)	0.91(0.61–1.35)	Nivolumab
0.91(0.67–1.23)	0.90(0.61–1.33)	0.99(0.73–1.33)	Pembrolizumab
0.71(0.57–0.88)	0.70(0.50–0.98)	0.77(0.62–0.96)	0.78(0.63–0.97)	CT
HR with 95%CI for PFS
Camrelizumab
0.87(0.64–1.19)	Pembrolizumab
0.69(0.48–1.00)	0.79(0.54–1.15)	Sintilimab
0.69(0.56–0.85)	0.79(0.63–0.99)	1.00(0.74–1.34)	CT
0.64(0.47–0.87)	0.73(0.54–1.00)	0.93(0.64–1.33)	0.93(0.75–1.15)	Nivolumab

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Abbreviations: HR, hazard ratios; CI, confidence interval; OS, overall survival; PFS, progression-free survival; T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care; AC, adenocarcinoma; SCC, squamous cell carcinoma.

In subgroup analysis of esophageal SCC (4 trials with 1458 patients receiving 5 treatments) (Table 5B), treatment with PD-1 inhibitors, including camrelizumab (HR = 0.71, 95% CI: 0.57–0.88), sintilimab (HR = 0.70, 95% CI: 0.50–0.98), nivolumab (HR = 0.77, 95% CI: 0.62–0.96), and pembrolizumab (HR = 0.78, 95% CI: 0.63–0.97), showed significant OS advantage over CT. Camrelizumab and pembrolizumab also significantly improved PFS when compared to CT (HR = 0.69, 95% CI: 0.56–0.85; and HR = 0.79, 95% CI: 0.63–0.99); camrelizumab also had significant PFS advantage over nivolumab (HR = 0.64, 95% CI: 0.47–0.87). According to treatment ranking (Table 4 and S3 Fig), camrelizumab was ranked the most effective treatment (0.73) in terms of OS, followed by sintilimab (0.73) and nivolumab (0.53); camrelizumab (0.94) remained the best treatment in terms of PFS, followed by pembrolizumab (0.78) and sintilimab (0.32).

Discussion

To the best of our knowledge, this is the first network meta-analysis that assessed the comparative efficacy of major treatments for previously treated patients with advanced esophageal/EGJ cancer. Our network meta-analysis showed that ramucirumab + CT and PD-1 inhibitors (camrelizumab, sintilimab, nivolumab, and pembrolizumab) conferred better OS than CT, while an OS benefit was not observed for PD-L1 inhibitor (avelumab) and other target agents (trastuzumab, everolimus, gefitinib, and anlotinib).

It should be noted that esophageal AC and SCC are generally considered to be two completely different diseases, with different molecular profiles, with distal esophageal AC showing almost the same molecular profile as junction AC [30]. In the RAINBOW trial [4], the addition of ramucirumab to CT significantly increased OS (HR = 0.52, 95% CI: 0.35–0.78) in patients with advanced EGJ AC. However, this regimen has not been tested in patients with SCC yet. More recently, several phase III trials have assessed the efficacy of PD-1/L1 inhibitors as second-line therapy in advanced esophageal or EGJ AC, but with inconsistent results. For example, pembrolizumab did not significantly improved OS, relative to CT, for patients with advanced EGJ AC in KEYNOTE-181 trial [14], but showed a positive result in KEYNOTE-061 study [12, 13]. Based on treatment ranking in terms of both OS and PFS in our network meta-analysis, ramucirumab + CT was ranked the best treatment in patients with esophageal or EGJ AC; PD-1/L1 inhibitors (pembrolizumab, nivolumab, and avelumab) were less effective than ramucirumab + CT. Conversely, PD-1 inhibitors, including camrelizumab [16], pembrolizumab [14], nivolumab [15], and sintilimab [17], have shown consistently significant longer OS than CT in previously treated patients with advanced esophageal SCC. In our network meta-analysis, despite the fact that no significant difference in OS was observed between these PD-1 inhibitors, camrelizumab was ranked the most effective treatment, either in OS or in PFS. These findings will be helpful for physicians to select more suitable therapy strategy in patients with different histological types.

Although PD-1 inhibitors have shown promising results in treatment of advanced esophageal SCC, they were likely to be more effective in patients with high PD-L1 levels. In the KEYNOTE-181 [14], pembrolizumab significantly improved OS vs CT as second-line therapy only for SCC patients with PD-L1 CPS ≥10. In ATTRACTION-3 [15], and ESCORT trials [16], despite nivolumab and camrelizumab showing OS advantage over CT, regardless of PD-L1 expression, patients with a high PD-L1 expression (CPS≥10 or PD-L1≥1) benefited more from PD-1 inhibitors. Predictive role of PD-L1 expression was also evaluated in patients with advanced esophageal/EGJ AC, but with inconsistent results. ATTRACTION-2 [10] and JAVELIN Gastric 300 [11] trials did not show a strong link between efficacy of nivolumab/avelumab and tumor PD-L1 level; meanwhile, long-term analysis of KEYNOTE-061 trial found that second-line pembrolizumab prolonged OS only among patients with PD-L1-positive esophageal/EGJ AC [12, 13]. Thus, PD-L1 expression, when used as a predictive biomarker for esophageal/EGJ AC, needs further evaluation.

Recently, the use of PD-1/L1 inhibitors, in combination with CT or CTLA-4 inhibitors, has demonstrated survival advantage over monotherapy in several tumors [31–34]. However, these combinations have never been assessed in advanced esophageal cancer. In the present meta-analysis, PD-1/L1 inhibitors, including nivolumab and avelumab, did not show a significant OS advantage over any of the treatments (except BSC/placebo) in patients with esophageal/EGJ AC; pembrolizumab significantly improved OS when compared to CT and some target agents, but with lesser efficacy than ramucirumab+CT. For esophageal SCC, although each PD-1 inhibitor monotherapy was superior to CT in individual trials, the difference was not significant for patients with low PD-L1 expression. Thus, there is a need for large phase III trials to assess whether PD-1/L1 inhibitors + CT could significantly improve survival when compared to monotherapy, especially for patients with advanced esophageal/EGJ AC and those with low PD-L1 expression.

Based on current findings, ramucirumab+CT and camrelizumab appeared to be the best second-line treatment for patients with esophageal/EGJ AC and esophageal SCC, respectively. However, this network meta-analysis has some limitations. First, the meta-analysis was conducted based on the results reported from trials rather than individual patient data, and on indirect comparisons instead of direct comparisons. In addition, PD-1 inhibitors are likely more effective for patients with SCC and tumors with high PD-L1 expression. For those with negative or low PD-L1 level tumors, whether PD-1 inhibitors are still superior to other treatments remain uncertain. Since all studies of targeted therapies did not report the PD-L1 expression level of the patients, we could not further assess the comparative efficacy according to PD-L1 expression status. Moreover, SAEs data for ramucirumab + CT was not provided in individual trials, and thus, we could not investigate the comparative safety profile of this treatment. All the limitations mentioned above do not allow us to reach a definitive conclusion about which was the best treatment, and our findings should be interpreted with caution. Second, different CT regimens and schedules used in individual trials were grouped together, which might lead to heterogeneity. Third, some of the newer data were extracted from recent conference abstracts [6, 8, 14, 17]. This could lead to a selection bias because more survival data might be reported in the full publication. Finally, most of the data for target agents were extracted from esophageal/EGJ cancer subgroups of studies involving participants with both esophageal/EGJ cancer and gastric cancer, which may result in bias.

Conclusions

Ramucirumab+CT and PD-1 inhibitors were superior to CT for previously treated advanced esophageal/EGJ cancer. Ramucirumab+CT seemed to be the most effective treatment in patients with esophageal/EGJ AC; moreover, PD-1 inhibitors, especially camrelizumab, were likely to be the optimal selection of treatments in patients with esophageal SCC. Future head-to-head comparison trials are needed to confirm these findings. There is also a need for phase III trials focusing on PD-1/L1 inhibitor-based combination therapy and treatment strategies in esophageal cancer patients with negative or low PD-L1 level tumors.

Supporting information

S1 Fig. Assessment of risk of bias.

a: Methodological quality graph: authors’ judgment about each methodological quality item presented as percentages across all included studies; b: Methodological quality summary: authors’ judgment about each methodological quality item for each included study, “+” low risk of bias; “?” unclear risk of bias; “-” high risk of bias.

(DOC)

Click here for additional data file.^{(1.2MB, doc)}

S2 Fig. Comparison-adjusted funnel plots of publication bias.

a, overall survival; b, progression-free survival. T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(793.5KB, doc)}

S3 Fig. Treatment ranking curves based on SUCRA.

OS, overall survival; PFS, progression-free survival; ORR, objective response rate; SAE, serious adverse event; SUCRA, surface under the cumulative ranking; T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(881KB, doc)}

S4 Fig. Assessment of transitivity among included trials.

a, sample size; b, median age; c, median follow up time. T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(1.5MB, doc)}

S5 Fig. Inconsistency evaluation by node-splitting analysis for overall survival.

CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(289KB, doc)}

S1 Table. PRISMA checklist.

(DOC)

Click here for additional data file.^{(67KB, doc)}

S2 Table. Search strategy.

(DOC)

Click here for additional data file.^{(101.5KB, doc)}

S3 Table. Comparisons of the fit of consistency and inconsistency models.

(DOC)

Click here for additional data file.^{(34KB, doc)}

S4 Table. Results of sensitivity analysis.

(DOC)

Click here for additional data file.^{(69KB, doc)}

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0252751.r001

Decision Letter 0

Ahmed Negida

30 Mar 2021

PONE-D-20-24414

Comparative efficiency of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer: a network meta-analysis

PLOS ONE

Dear Dr. Dang,

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Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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Reviewer #1: I Don't Know

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Reviewer #4: I Don't Know

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: No

**********

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Reviewer #1: The authors need to clarify the investigator(s) who actually performed the statistical analyses.

The authors need to further expand on the challenges associated with data from abstract presentations only in this type of analysis.

Reviewer #2: The research method is appropriate and the research process is complete, but the research innovation is insufficient, so the selection of articles needs to be further optimized. The depth of research is not enough, and further analysis is needed.

Reviewer #3: In this manuscript, the authors made a network meta-analysis about comparative efficiency of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer.

Major revision:

1. There was no quality assessment of the included studies;

2. The charts of sensitivity analysis and heterogeneity analysis were not provided.

Reviewer #4: Based on the systematic paper review, the authors conducted a network meta-analysis to investigate which the most effective treatment for previously treated patients with advanced esophageal and esophagogastic junction cancer. They found that Ramucirumab+CT and PD-1 inhibitors were superior to CT for previously treated advanced esophageal/EGJ cancer. I think the data is valuable. They also discuss the limitation of the current study and pointing out future directions to confirm the results found in the current study.

Page 11, the first time use of network meta-analysis need to be the full name other that the abbreviation.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

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Attachment

Submitted filename: reviewer.docx

Click here for additional data file.^{(11.3KB, docx)}

PLoS One. 2021 Jun 4;16(6):e0252751. doi: 10.1371/journal.pone.0252751.r002

Author response to Decision Letter 0

8 Apr 2021

5. Review Comments to the Author

Reviewer #1: The authors need to clarify the investigator(s) who actually performed the statistical analyses.

The authors need to further expand on the challenges associated with data from abstract presentations only in this type of analysis.

Response: The statistical analyses were performed by two investigators (SL and TL), and we have added the sentence to the manuscript (page, line). According to the reviewer’s request, we have further discussed limitations of our findings in the last paragraph of Discussion section, as below:

Based on current findings, Ramucirumab+CT and camrelizumab appeared to be the best second-line treatment for patients with esophageal/EGJ AC and esophageal SCC, respectively. However, this network meta-analysis has some limitations. First, the meta-analysis was conducted based on the results reported from trials rather than individual patient data, and on indirect comparisons instead of direct comparisons. In addition, PD-1 inhibitors are likely more effective for patients with SCC and tumors with high PD-L1 expression. For those with negative or low PD-L1 level tumors, whether PD-1 inhibitors are still superior to other treatments remain uncertain. Since all studies of targeted therapies did not report the PD-L1 expression level of the patients, we could not further assess the comparative efficacy according to PD-L1 expression status. Moreover, SAEs data for Ramucirumab + CT was not provided in individual trials, and thus, we could not investigate the comparative safety profile of this treatment. All the limitations mentioned above do not allow us to reach a definitive conclusion about which was the best treatment, and our findings should be interpreted with caution.

We have tried to present our findings in more probabilistic terms, for example, using words of “seem to be”, or “is likely to be”, etc.

Response: With regard to the research innovation of our study, perhaps not be sufficient enough just like the reviewer pointed out, we would like to present some points as below. For patients with esophageal squamous cell carcinoma (SCC), four phase III trials have consistently demonstrated that PD-1inhibitors (including camrelizumab, sintilimab, nivolumab, and pembrolizumab) are superior to CT. However, whether there are difference in efficacy between the four PD-1inhibitors and which might be a better selection for this set of patients remain uncertain. For patients with esophageal or EGJ adenocarcinoma (AC), there are also four phase III trials assessing efficacy of PD-1/PD-L1 inhibitors, but with inconsistent results. Whether PD-1/PD-L1 inhibitors are more effective than other targeted therapies esophageal or EGJ AC is also unclear. In light of these issues, and due to lack of head-to-head comparison trials, we performed the network meta-analysis, attempting to identify the most preferable treatment for patients with esophageal/EGJ AC and esophageal SCC, respectively. To our knowledge, this is the first network meta-analysis focusing on this subject. We found that Ramucirumab+CT seemed to be the most effective treatment in patients with esophageal/EGJ AC; while PD-1 inhibitors, especially camrelizumab, were likely to be the optimal selection of treatments in patients with esophageal SCC. Nevertheless, This study has some limitations which we have re-discussed in the last paragraph of Discussion section. The main limitation was that the meta-analysis was conducted based on results reported from trials rather than individual patient data, and based on indirect comparisons but not direct comparisons. In addition, PD-1 inhibitors are likely more effective for patients with SCC and tumors with high PD-L1 expression. For those with negative or low PD-L1 level tumors, whether PD-1 inhibitors are still superior to other treatments remain uncertain. Moreover, SAEs data for Ramucirumab + CT was not provided in individual trials, and thus, we could not investigate the comparative safety profile of this treatment. All the limitations mentioned above do not allow us to reach a definitive conclusion about which was the best treatment, and our findings should be interpreted with caution.

Due to that all studies of targeted therapies did not report patients PD-L1 expression level, we could not further assess the comparative efficacy according to PD-L1 expression status. There is a need for additional phase III trials focusing on this subject.

In term of the selection of articles, all phase II and III randomized controlled trials which compared ICIs or targeted therapies with CT or BSC/placebo were included in our study, and retrospective study, phase I trials, and non-randomized trials were excluded. To achieve the network of eligible treatment comparisons, two phase III trials [28,29] which assessed CT vs BSC/placebo were also included because the control arm in several trials assessing efficacy of target agents (anlotinib, everolimus, gefitinib, and ramucirumab) was BSC/placebo. That is, the two trials actually acted as a “bridge” in this network meta-analysis.

Fig 2 Network of eligible comparisons for the network meta-analysis. a, overall survival; b, progression-free survival. T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

Major revision:

1. There was no quality assessment of the included studies;

2. The charts of sensitivity analysis and heterogeneity analysis were not provided.

Response: Quality assessment (S1 and S2 Fig), sensitivity analysis (S4 Table), transitivity (S4 Fig), and inconsistency (S3 Table and S5 Fig) can be found in Supporting information. Pathological type (esophageal adenocarcinoma and squamous cell carcinoma) might account for a part of heterogeneity, and we had performed the subgroup analyses accordingly. Besides, different CT regimens and schedules used in individual trials might also lead to heterogeneity, which had been discussed as a limitation in the last paragraph of Discussion section.

Page 11, the first time use of network meta-analysis need to be the full name other that the abbreviation.

Response: We have revised it.

Attachment

Submitted filename: Response to reviewers.doc

Click here for additional data file.^{(8.4MB, doc)}

PLoS One. doi: 10.1371/journal.pone.0252751.r003

Decision Letter 1

Ahmed Negida

24 May 2021

Comparative efficacy of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer: a network meta-analysis

PONE-D-20-24414R1

Dear Dr. Dang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Ahmed Negida, MD

Academic Editor

PLOS ONE

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1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

Reviewer #4: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

Reviewer #4: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: Yes

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

Reviewer #4: Yes

**********

6. Review Comments to the Author

Reviewer #3: (No Response)

Reviewer #4: This draft of the manuscript includes good solutions to the issues identified in the previous draft.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: Yes: Wei Liu

Reviewer #4: No

PLoS One. doi: 10.1371/journal.pone.0252751.r004

Acceptance letter

Ahmed Negida

27 May 2021

PONE-D-20-24414R1

Comparative efficacy of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer: a network meta-analysis

Dear Dr. Dang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ahmed Negida

%CORR_ED_EDITOR_ROLE%

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Assessment of risk of bias.

(DOC)

Click here for additional data file.^{(1.2MB, doc)}

S2 Fig. Comparison-adjusted funnel plots of publication bias.

a, overall survival; b, progression-free survival. T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(793.5KB, doc)}

S3 Fig. Treatment ranking curves based on SUCRA.

(DOC)

Click here for additional data file.^{(881KB, doc)}

S4 Fig. Assessment of transitivity among included trials.

a, sample size; b, median age; c, median follow up time. T-DXd, trastuzumab deruxtecan; CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(1.5MB, doc)}

S5 Fig. Inconsistency evaluation by node-splitting analysis for overall survival.

CT, chemotherapy; BSC, best supportive care.

(DOC)

Click here for additional data file.^{(289KB, doc)}

S1 Table. PRISMA checklist.

(DOC)

Click here for additional data file.^{(67KB, doc)}

S2 Table. Search strategy.

(DOC)

Click here for additional data file.^{(101.5KB, doc)}

S3 Table. Comparisons of the fit of consistency and inconsistency models.

(DOC)

Click here for additional data file.^{(34KB, doc)}

S4 Table. Results of sensitivity analysis.

(DOC)

Click here for additional data file.^{(69KB, doc)}

Attachment

Submitted filename: reviewer.docx

Click here for additional data file.^{(11.3KB, docx)}

Attachment

Submitted filename: Response to reviewers.doc

Click here for additional data file.^{(8.4MB, doc)}

Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

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PERMALINK

Comparative efficacy of treatments for previously treated patients with advanced esophageal and esophagogastric junction cancer: A network meta-analysis

Shuiyu Lin

Tingting Liu

Jun Chen

Guang Li

Jun Dang

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Methods

Literature search strategy

Inclusion and exclusion criteria

Data extraction

Quality assessment

Statistical analysis

Results

Literature search results and characteristics of included RCTs

Fig 1. Literature search and selection.

Table 1. Characteristics of included trials.

Assessment of included trial

Conventional pairwise meta-analysis

Table 2. Results of single trial and direct comparison meta-analysis.

Network meta-analysis

Fig 2. Network of eligible comparisons for the network meta-analysis.

Table 3. Results of network meta-analysis.

Table 4. Treatment ranking.

Transitivity, inconsistency, and sensitivity analysis

Subgroup analysis

Table 5. Indirect results of subgroup analysis according to histological type.

Discussion

Conclusions

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Ahmed Negida

Roles

Author response to Decision Letter 0

Decision Letter 1

Ahmed Negida

Roles

Acceptance letter

Ahmed Negida

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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