Prognostic and clinicopathological value of systemic inflammation response index (SIRI) in patients with breast cancer: a meta-analysis

Abstract

Background

Many studies have explored the value of the systemic inflammation response index (SIRI) in predicting the prognosis of patients with breast cancer (BC); however, their findings remain controversial. Consequently, we performed the present meta-analysis to accurately identify the role of SIRI in predicting BC prognosis.

Methods

PubMed, Embase, Cochrane Library, and Web of Science databases were comprehensively searched between their inception and February 10, 2024. The significance of SIRI in predicting overall survival (OS) and disease-free survival (DFS) in BC patients was analyzed by calculating pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs).

Results

Eight articles involving 2,997 patients with BC were enrolled in the present study. According to our combined analysis, a higher SIRI was markedly associated with dismal OS (HR = 2.43, 95%CI = 1.42–4.15, p < 0.001) but not poor DFS (HR = 2.59, 95%CI = 0.81–8.24, p = 0.107) in patients with BC. Moreover, based on the pooled results, a high SIRI was significantly related to T3–T4 stage (OR = 1.73, 95%CI = 1.40–2.14, p < 0.001), N1–N3 stage (OR = 1.61, 95%CI = 1.37–1.91, p < 0.001), TNM stage III (OR = 1.63, 95%CI = 1.34–1.98, p < 0.001), and poor differentiation (OR = 1.25, 95%CI = 1.02–1.52, p = 0.028).

Conclusion

According to our results, a high SIRI significantly predicted poor OS in patients with BC. Furthermore, elevated SIRI was also remarkably related to increased tumor size and later BC tumor stage. The SIRI can serve as a novel prognostic biomarker for patients with BC.

KEY MESSAGES

1. Based on our knowledge, this study is the first meta-analysis to explore value of SIRI in predicting BC prognosis.

2. According to our results, a high SIRI significantly predicted the dismal OS in BC patients.

3. SIRI can serve as the novel prognostic biomarker for BC patients.

Keywords:

• Systemic inflammation response index
• breast cancer
• meta-analysis
• survival
• biomarkers

Introduction

Breast cancer (BC) has the highest morbidity among female malignancies worldwide and is also a leading cause of morbidity and mortality [1]. According to GLOBOCAN estimates, there were 2,261,419 newly diagnosed BC cases and 684,996 deaths globally by 2020 [2]. There has been an increase in BC incidence worldwide, which has increased the burden on the healthcare system [1]. Four histological subtypes of BC exist: triple-negative, overexpressed HER2 (human epidermal growth factor receptor 2), luminal A, and luminal B [3]. In the last several decades, intensive fundamental and clinical studies have significantly improved the efficacy of surgical treatment, radiotherapy, chemotherapy, immunotherapy, and targeted therapy in the treatment of BC [3]. Nonetheless, advances in the prediction of prognosis for BC remain disappointing. Therefore, the development of creditable, operable, and cost-effective prognostic biomarkers for BC is necessary for guiding clinicians and individualized treatment plans.

Current evidence shows that chronic inflammation is inseparable from tumorigenesis, proliferation, infiltration, metastasis, and apoptosis at various stages [4, 5]. Recent studies have demonstrated that diverse blood-based inflammation parameters, such as platelet-to-lymphocyte ratio [6], lymphocyte-to-monocyte ratio [7], C-reactive protein-to-albumin ratio [8], prognostic nutritional index [9], and systemic inflammation response index (SIRI) [10] have significant value in predicting the prognosis of many solid tumors. The SIRI can be determined as SIRI = neutrophil count × monocyte count/lymphocyte count. It represents a novel prognostic marker that was first introduced by Qi et al. in 2016 for pancreatic cancer prognosis [11]. Recent studies have reported the prognostic effect of SIRI for various cancers, including nasopharyngeal carcinoma (NPC) [12], colorectal [13], ovarian [14], gastric [15], and bladder cancers [16]. Many previous studies have explored the significance of the SIRI in predicting BC prognosis, but no consistent findings have been obtained [17–24]. For instance, an increased SIRI has been reported in certain studies as a significant prognostic marker for BC [17, 18, 20], but others did not find any obvious association between SIRI and BC prognosis [19, 22]. Consequently, this meta-analysis was performed to identify the accurate role of SIRI in predicting BC prognosis. Furthermore, we assessed the relationship between SIRI and clinicopathological characteristics of BC.

Materials and methods

Study guideline

The present study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [25] (Supplementary File S1). The study protocol was registered with INPLASY under registration number INPLASY2023120039. The registration is available at https://inplasy.com/inplasy-2023-12-0039/.

Ethnic statement

Informed consent and ethical approval were not required in this study because it was a meta-analysis and did not involve individual participants.

Search strategy

In this study, we comprehensively searched PubMed, Embase, Cochrane Library, and Web of Science databases between inception and February 10, 2024, using the following search strategies: (system inflammation response index, systemic inflammation response index, or systemic inflammatory response index) and (breast carcinoma, breast tumor, breast cancer, or breast tumors). The detailed search strategy for each database is shown in Supplementary File 2. The language used was restricted to English. A manual search of relevant studies and reviews was conducted to identify additional eligible studies.

Selection criteria

The following studies were included: (1) BC was diagnosed based on pathology; (2) reports of the association of SIRI with BC prognosis; (3) outcomes of interest, including but not limited to overall survival (OS), cancer-specific survival, disease-free survival (DFS), and progression-free survival (PFS); (4) studies with available or calculable hazard ratios (HRs) and 95% confidence intervals (CIs); (5) studies identifying the threshold SIRI; and (6) English publications. The following studies were excluded: (1) reviews, meeting abstracts, comments, case reports, and letters; (2) studies with duplicate patients; and (3) animal studies.

Data collection and quality evaluation

Data were collected in each qualified study by two researchers (SZ and TC). Any discrepancy was settled by negotiation until a consensus was reached. The following data were collected from each publication: first author’s name, publication year, age, country, sample size, study design, study period, tumor-node-metastasis (TNM) classification, treatment, threshold SIRI, follow-up, survival endpoints, survival analysis, cut-off value determination method, and HRs with 95%CIs. The primary and secondary survival end points were OS and DFS, respectively. The Newcastle-Ottawa Scale (NOS) was employed to evaluate the enrolled study quality [26], with a score ranging from to 0–9, and a NOS score >6 suggested high-quality studies.

Statistical analysis

We computed combined HRs and 95%CIs to estimate the role of SIRI in determining the OS and DFS of patients with BC. Between-study heterogeneity was evaluated using Cochran’s Q and Higgin’s I² tests. I² > 50% or p < 0.10 stood for obvious heterogeneity, so we adopted the random-effects model; otherwise, we employed the fixed-effects model. Subgroup analysis was performed to detect potential sources of heterogeneity. The correlation between SIRI and the clinicopathological characteristics of BC was assessed by pooling the ORs and 95%CIs. To assess the stability of the combined data and to determine the cause of heterogeneity, a sensitivity analysis was conducted. Publication bias was estimated using Begg’s and Egger’s tests. Statistical analysis was conducted using Stata software (version 12.0; StataCorp LP, College Station, TX, USA). Statistical significance was set at p < 0.05.

Results

Study retrieval procedure

As shown in Figure 1, there were 420 articles obtained from the primary database search. Duplicates were removed to obtain a total of 303 studies. Through title and abstract screening, we eliminated 277 studies owing to irrelevance or animal studies. The remaining 26 studies were examined by full-text reading. Seventeen studies were excluded for the following reasons: not on SIRI (n = 15), duplicate patients (n = 2), and no survival data (n = 1). Ultimately, this meta-analysis recruited eight articles involving 2,997 BC patients [17–24] (Figure 1).

Figure 1. PRISMA diagram of literature search and study inclusion.

Study characteristics

Table 1 presents the baseline features of the eligible studies. Six studies were carried out in China [17–21, 23] and one each was carried out in Japan [22] and Taiwan [24]. They were published between 2020 and 2024, and were all retrospective studies. The sample size ranged from 46 to 949, with a median value of 270. Six studies recruited patients with stage I-III [17–19, 21, 23, 24], one study enrolled stage II-III patients [20], whereas one study included stage IV patients [22]. Five studies treated patients with neoadjuvant chemotherapy (NACT)+ surgery [19–21, 23, 24], two studies used surgery [17, 18], and one study applied chemotherapy [22]. All included studies used receiver operating characteristic (ROC) curves to determine the threshold SIRI (range, 0.465–1.6; median, 0.725) [17–24]. Six articles mentioned the role of SIRI in predicting the OS of BC [17, 18, 20–22, 24]. Five studies presented the relationship between SIRI and DFS of BC [17, 19, 21, 23, 24]. For the eligible articles were 6–8 (median, 7.5), implying their high quality (Table 1).

Table 1. The basic characteristics of included studies.

Author	Year	Country/region	Sample size	Age (years) Median(range)	Study design	Study period	TNM stage	Treatment	Cut-off value of SIRI	Follow-up (months) Median(range)	Survival endpoints	Survival analysis	NOS score
Hua, X.	2020	China	390	68(49–87)	Retrospective	2010–2012	I–III	Surgery	0.54	65.5(0.9–95.9)	OS, DFS	Multivariate	8
Wang, L.	2020	China	949	54(24–89)	Retrospective	2009–2012	I–III	Surgery	0.65	102	OS	Multivariate	7
He, Q.	2021	China	47	52	Retrospective	2016–2020	I–III	NACT + surgery	0.465	10	DFS	Univariate	6
Jiang, C.	2022	China	280	49	Retrospective	2012–2016	II–III	NACT + surgery	0.52	1–120	OS	Multivariate	8
Zhu, M.	2022	China	785	47(22–82)	Retrospective	1998–2016	I–III	NACT + surgery	0.80	1–250	OS, DFS	Multivariate	8
Huang, W.	2023	China	260	46.5(25–76)	Retrospective	2014–2018	I–III	NACT + surgery	1.6	40(1–94)	DFS	Multivariate	7
Yamanouchi, K.	2023	Japan	46	57(38–73)	Retrospective	2008–2020	IV	Chemotherapy	0.83	30(1–146)	OS	Multivariate	7
Wu, H. Y.	2024	Taiwan	240	53(25–79)	Retrospective	2011–2021	I–III	NACT + surgery	1.27	1–140	OS, DFS	Univariate	8

TNM: tumor, node, metastasis; NACT: neoadjuvant chemotherapy; SIRI: systemic inflammation response index; OS: overall survival; DFS: disease-free survival; NOS: Newcastle-Ottawa Scale.

SIRI and OS in BC

Altogether, six articles involving 2,690 patients [17, 18, 20–22, 24] reported the value of SIRI in predicting the OS of BC patients. In included studies [17, 18, 20–22, 24], five studies [17, 18, 20, 21, 24] reported that high SIRI was significantly associated with poor OS in BC patients. Whereas one study showed that there was no significant correlation between SIRI and OS in BC22 (Figure 2). Because of significant heterogeneity (I² = 86.0%, p < 0.001), we applied the random-effects model. According to the combined data in Figure 2, an increased SIRI was related to dismal OS in BC (HR = 2.43, 95%CI = 1.42–4.15, p < 0.001). Based on the subgroup analyses, the significance of SIRI in predicting OS remained unaffected by sample size or survival analysis types (p < 0.05) (Table 2). Furthermore, an increased SIRI independently predicted PS in the following subgroups: studies carried out in China (p < 0.001), TNM stage I-III (p = 0.002), cut-off value <0.80 (p < 0.001), and patients receiving surgery (p < 0.001) or NACT + surgery (p = 0.030) (Table 2).

Figure 2. Forest plot of meta-analysis of the relationship between SIRI and OS in patients with BC.

Table 2. Subgroup analysis of the prognostic value of SIRI for OS in patients with breast cancer.

Subgroups	No. of studies	No. of patients	Effects model	HR (95%CI)	p	Heterogeneity
						I^2 (%)	Ph
Total	6	2,690	Random	2.43(1.42–4.15)	0.001	86.0	<0.001
Country/region
China	4	2,404	Fixed	1.76(1.48–2.10)	<0.001	0	0.498
Japan	1	46	–	0.37(0.03–4.47)	0.434	–	–
Taiwan	1	240	–	6.53(4.29–9.96)	<0.001	–	–
Sample size
<300	3	566	Random	3.55(1.13–11.13)	0.030	62.9	0.008
≥300	3	2,124	Fixed	1.73(1.45–2.07)	<0.001	0	0.667
TNM stage
I–III	4	2,595	Random	2.50(1.39–4.48)	0.002	90.9	<0.001
II–III	1	49	–	3.88(1.11–13.55)	0.033	–	–
IV	1	46	–	0.37(0.03–4.47)	0.434	–	–
Treatment
Surgery	2	1,339	Fixed	1.83(1.43–2.36)	<0.001	0	0.515
NACT + surgery	3	1,305	Random	3.39(1.13–10.16)	0.030	93.5	<0.001
Chemotherapy	1	46	–	0.37(0.03–4.47)	0.434	–	–
Cut-off value
<0.80	3	1,619	Fixed	1.89(1.48–2.42)	<0.001	0	0.416
≥0.80	3	1,071	Random	2.29(0.66–7.98)	0.193	93.8	<0.001
Survival analysis
Univariate	1	240	–	6.63(4.29–9.96)	<0.001	–	–
Multivariate	5	2,450	Fixed	1.75(1.47–2.09)	<0.001	0	0.423

TNM: tumor, node, metastasis; NACT: neoadjuvant chemotherapy; SIRI: systemic inflammation response index; OS: overall survival.

SIRI and DFS in BC

Five studies comprising 1,722 patients [17, 19, 21, 23, 24] provided data on the correlation between SIRI and DFS. Of the enrolled studies [17, 19, 21, 23, 24], three studies [21, 23, 24] identified elevated SIRI as a significant prognostic marker for DFS in BC. However, two studies [17, 19] reported that there was non-significant relationship between SIRI and DFS in BC (Figure 3). We used a random-effects model because of significant heterogeneity (I² = 96.6%, p < 0.001). Pooled results according to Figure 3 and Table 3 were HR = 2.59, 95%CI = 0.81–8.24, p = 0.107, suggesting that high SIRI has non-significant association with DFS of BC. Subgroup analysis showed that increased SIRI still significantly predicted poor DFS in the following subgroups: studies carried out in China (p = 0.001), studies carried out in Taiwan (p < 0.001), sample size ≥ 300 (p = 0.008), univariate analysis (p < 0.001), and multivariate survival analysis (p = 0.001) (Table 3).

Figure 3. Forest plot of meta-analysis of the relationship between SIRI and DFS in patients with BC.

Table 3. Subgroup analysis of the prognostic value of SIRI for DFS in patients with breast cancer.

Subgroups	No. of studies	No. of patients	Effects model	HR (95%CI)	p	Heterogeneity
						I^2(%)	Ph
Total	5	1,722	Random	2.59(0.81–8.24)	0.107	96.6	<0.001
Country/region
China	4	1,482	Fixed	1.51(1.19–1.91)	0.001	0	0.751
Taiwan	1	240	–	10.32(8.01–13.30)	<0.001	–	–
Sample size
<300	3	547	Random	4.71(0.91–24.25)	0.064	93.8	<0.001
≥300	2	1,175	Fixed	1.43(1.10–1.87)	0.008	0	0.722
Treatment
Surgery	1	390	–	1.32(0.78–2.23)	0.298	–	–
NACT + surgery	4	1,332	Random	3.22(0.80–12.88)	0.098	97.1	<0.001
Cut-off value
<0.80	2	437	Fixed	1.34(0.79–2.25)	0.279	0	0.492
≥0.80	3	1,285	Random	3.06(0.75–12.51)	0.120	98.0	<0.001
Survival analysis
Univariate	2	287	Fixed	10.33(8.02–13.31)	<0.001	0	0.813
Multivariate	3	1,435	Fixed	1.50(1.19–1.91)	0.001	0	0.679

TNM: tumor, node, metastasis; NACT: neoadjuvant chemotherapy; SIRI: systemic inflammation response index; DFS: disease-free survival.

The correlation between SIRI and clinicopathological factors of BC

Altogether, six studies with 2,904 patients [17, 18, 20, 21, 23, 24] reported a relationship between SIRI and clinicopathological characteristics of BC. As shown by the pooled results in Table 4, Figures 4, and 5 an increased SIRI was markedly related to T3–T4 stage (OR = 1.73, 95%CI = 1.40–2.14, p < 0.001), N1–N3 stage (OR = 1.61, 95%CI = 1.37–1.91, p < 0.001), TNM stage III (OR = 1.63, 95%CI = 1.34–1.98, p < 0.001), and poor differentiation (OR = 1.25, 95%CI = 1.02–1.52, p = 0.028). However, SIRI was not significantly related to age (OR = 0.87, 95%CI = 0.74–1.02, p = 0.095), estrogen receptor (ER) status (OR = 0.78, 95%CI = 0.54–1.14, p = 0.200), progesterone receptor (PR) status (OR = 0.88, 95%CI = 0.52–1.47, p = 0.617), or HER2 status (OR = 0.99, 95%CI = 0.81–1.20, p = 0.912) (Table 4, Figures 4, and 5).

Figure 4. Forest plots of the correlations between SIRI and clinicopathological features in BC. (A) Age (year) (≥50 vs <50); (B) T stage (T3–T4 vs T1–T2); (C) N stage (N1–N3 vs N0); and (D) TNM stage (III vs I-II).

Figure 5. Forest plots of the correlations between SIRI and clinicopathological features in BC. (A) ER status (positive vs negative); (B) PR status (positive vs negative); (C) HER2 status (positive vs negative); and (D) Differentiation (poor vs well/moderate).

Table 4. The association between SIRI and clinicopathological features in patients with breast cancer.

Clinicopathological factors	No. of studies	No. of patients	Effects model	OR (95%CI)	p	Heterogeneity
						I^2(%)	Ph
Age (year) (≥50 vs <50)	5	2,664	Fixed	0.87(0.74–1.02)	0.095	1.0	0.401
T stage (T3–T4 vs T1–T2)	6	2,904	Fixed	1.73(1.40–2.14)	<0.001	33.6	0.184
N stage (N1–N3 vs N0)	6	2,904	Fixed	1.61(1.37–1.91)	<0.001	17.8	0.298
TNM stage (III vs I–II)	5	2,664	Fixed	1.63(1.34–1.98)	<0.001	42.5	0.139
ER status (positive vs negative)	4	1,879	Random	0.78(0.54–1.14)	0.200	62.1	0.048
PR status (positive vs negative)	4	1,879	Random	0.88(0.52–1.47)	0.617	81.6	0.001
HER2 status (positive vs negative)	5	2,119	Fixed	0.99(0.81–1.20)	0.912	0	0.980
Differentiation (poor vs well/moderate)	3	1,994	Fixed	1.25(1.02–1.52)	0.028	79.6	0.242

TNM: tumor, node, metastasis; ER: estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor-2; SIRI: systemic inflammation response index.

Sensitivity analysis

We conducted a sensitivity analysis by omitting each study in turn. The HR for each component analysis was within the predicted range in the remaining studies. Consequently, the reliability of the meta-analysis was verified (Figure 6).

Figure 6. Sensitivity analyses of outcomes. (A) OS. (B) DFS.

Publication bias

To assess publication bias, we pooled HRs and 95% CIs for OS and DFS using funnel plots and the Begg’s and Egger’s tests. As shown in Figure 7, funnel plots exhibited symmetry for OS and DFS. Moreover, obvious publication bias was not detected for OS p = 0.452 and 0.709 upon Begg’s and Egger’s tests separately) or DFS (p = 0.806 and 0.606 upon Begg’s and Egger’s tests separately) (Figure 7).

Figure 7. Publication bias tested by Begg’s test and Egger’s test. (A) Begg’s test for OS, p = 0.452; (B) Egger’s test for OS, p = 0.709; (C) Begg’s test for DFS, p = 0.806; and (D) Egger’s test for DFS, p = 0.606.

Discussion

The significance of SIRI in predicting BC prognosis is inconsistent among previous studies. We included eight articles involving 2,997 patients in this work [17–24] and aggregated the HRs and 95%CIs. According to our results, an increased SIRI significantly predicted poor OS in patients with BC. Moreover, elevated SIRI was significantly associated with T3–T4 stage, N1–N3 stage, TNM stage III, and poor tumor differentiation in patients with BC. As revealed by the publication bias test, the findings of this study were reliable. Taken together, SIRI is an effective and reliable factor for predicting the long-term prognosis of BC patients. To the best of our knowledge, this study is the first meta-analysis to explore the value of SIRI in predicting BC prognosis.

An increased SIRI can be the result of increased neutrophil and monocyte counts, and/or decreased lymphocyte counts. Although the precise mechanisms underlying the role of SIRI in predicting BC prognosis have not been clarified, they can be interpreted as follows. First, neutrophils have been extensively recognized to have a critical effect on the promotion of tumor cell proliferation, migration, invasion, and immunosuppression during the carcinogenesis process [27, 28]. As a result of the release of chemokines and cytokines such as vascular endothelial growth factor (VEGF), neutrophils can accelerate angiogenesis, enhance tumor cell adhesion, and promote distant metastasis of tumor [29]. Second, monocytes, particularly cells that differentiate into tumor-associated macrophages (TAMs), participate in tumorigenesis. Through the production of proinflammatory cytokines and stimulation of tumor angiogenesis, TAMs can accelerate tumor growth [30]. Third, among the body’s immune system components, lymphocytes are capable of inhibiting tumorigenesis and relapse as well as regulating immune function through cytokines and cytotoxic death [31]. Lymphocytes such as CD4+ and CD8+ cells are important for cellular immunity. Tumor-infiltrating T lymphocytes inhibit tumor cell growth and invasion by enhancing their apoptosis [32]. Therefore, a high SIRI can be a factor in predicting poor prognosis in patients with BC.

Notably, the cut-off values of SIRI are not uniform in included studies. All enrolled studies used ROC curves to determine the optimal cut-off value of SIRI. The cut-off values ranged from 0.465 to 1.6 [17–24], with a median value of 0.725. Due to the heterogeneity of recruited patients, the ROC curve identified various cut-off values in each study. A standard cut-off value of SIRI is still needed to improve the applicability of this index. The application of various cut-off values of SIRI in the included studies could be a reason of the different results in these studies [17–24].

Recently, many articles have mentioned the significant role of SIRI in predicting the prognosis of different cancer types through meta-analysis [33–36]. Recently, as reported in a meta-analysis involving 3,187 patients, SIRI independently predicted the dismal OS of NPC [33]. In another meta-analysis including 30 studies, an increased SIRI was markedly related to poor OS and DFS in patients with gastrointestinal tumor patients [34]. According to Zhou et al. a high SIRI was related to short OS and DFS/recurrence-free survival/PFS in solid tumor patients in their meta-analysis comprising 10,754 cases [36]. Our BC results conformed to the significance of SIRI in predicting additional cancer types.

Some limitations of the present study should be noted. First, it had a small sample size. Although we retrieved the latest literature. Second, all the qualified articles were published in Asian regions. Consequently, our results may be applicable to Asian patients with BC. Third, the threshold SIRI was not uniform among the included studies. A standard cut-off value of the SIRI for BC is still needed.

Conclusions

In summary, this meta-analysis demonstrated that increased SIRI notably predicted poor OS in patients with BC. Additionally, elevated SIRI was also related to increased tumor size and an advanced BC tumor stage. SIRI is a novel prognostic biomarker in patients with BC. BC patients with high pretreatment SIRI experience high risk of poor survival and tumor progression. As revealed in this meta-analysis, for BC patients with SIRI ≥0.80, systematic therapy including NACT and surgery may be beneficial. Furthermore, a standard SIRI cut-off value should be determined in future studies. Owing to some limitations, large-scale international multicenter trials should be conducted for further validation of our results.

Authors contributions

SZ conceived the study. SZ and TC performed the database search, literature review, study selection, quality evaluation, and data collection. SZ and TC performed statistical analysis and interpreted the results. SZ drafted the manuscript. All authors have contributed to the manuscript and approved the submitted version.

Abbreviations
SIRI	=	systemic inflammation response index
BC	=	breast cancer
HR	=	hazard ratio
CI	=	confidence interval
OS	=	overall survival
DFS	=	disease-free survival
HER2	=	human epidermal growth factor receptor 2
NPC	=	nasopharyngeal carcinoma
PRISMA	=	Preferred Reporting Items for Systematic Reviews and Meta-Analyses
TNM	=	tumor-node-metastasis
NOS	=	Newcastle-Ottawa Scale
NACT	=	neoadjuvant chemotherapy
ROC	=	receiver operating characteristic
VEGF	=	vascular endothelial growth factor
TAMs	=	tumor-associated macrophage

Disclosure statement

The authors declare that there is no conflict of interest.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.