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. 2024 May 13;19(5):e0302685. doi: 10.1371/journal.pone.0302685

Effect of chemotherapy on prognosis in patients with primary pancreatic signet ring cell carcinoma: A large real-world study based on machine learning

Kun Huang 1,*,#, Xinzhu Yuan 2,#, Pingwu Zhao 1, Yunshen He 1
Editor: Filomena de Nigris3
PMCID: PMC11090313  PMID: 38739633

Abstract

Background

Primary pancreatic signet ring cell carcinoma (PSRCC), an extremely rare histologic variant of pancreatic cancer, has a poor prognosis. This study aimed to investigate the prognostic value of chemotherapy in PSRCC.

Methods

Patients with PSRCC between 2000 and 2019 were identified using the Surveillance Epidemiology and End Results (SEER) database. The main outcomes in this study were cancer-specific survival (CSS) and overall survival (OS). The baseline characteristics of patients were compared using Pearson’s Chi-square test. Kaplan-Meier analysis was used to generate the survival curves. Least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression models, and Random Survival Forest model were used to analyze the prognostic variables for OS and CSS. The variance inflation factors (VIFs) were used to analyze whether there was an overfitting problem.

Results

A total of 588 patients were identified. Chemotherapy was an independent prognostic factor for OS and CSS, and significantly associated with OS (HR = 0.33, 95% CI = 0.27–0.40, P <0.001) and CSS (HR = 0.32, 95% CI = 0.26–0.39, P <0.001).

Conclusions

Chemotherapy showed beneficial effects on OS and CSS in patients with PSRCC and should be recommended in clinical practice.

Introduction

Pancreatic cancer, the fourth leading cause of cancer death in Europe and the United States [1–4], is a highly malignant tumor with an insidious onset. The incidence and mortality of the cancer showed a continuously increasing trend in China during 1990–2020, and were 8.32/100,000 and 8.48/100,000, respectively in 2020 [5]. On the other hand, the prognosis of pancreatic cancer remains poor with a 5-year survival of 11.5% [6]. Primary pancreatic signet ring cell carcinoma (PSRCC), occurring in less than 1% of pancreatic cancers, is an extremely rare histologic variant with a worse prognosis [7]. Due to the low prevalence, treatment guidelines specific to PSRCC do not exist. In clinical practice, the therapy is guided by existing literature on pancreatic cancer [8]. Surgery and chemotherapy are the main treatment for pancreatic cancer [9]. However, nearly half of the patients had distant metastasis at the time of initial diagnosis, thus losing the opportunity for surgery [10–12]. The value of chemotherapy in PSRCC is still unclear, with the lack of high-quality clinical evidence and large samples of multicenter clinical studies. In this study, we used real-world data from the American Surveillance, Epidemiology, and End Results (SEER) database to investigate the prognostic value of chemotherapy for patients with PSRCC [13].

Patients and methods

Patients selection

The SEER‑17 Regs Research Plus Data released in April 2022 was retrieved using the SEER*Stat software version 8.4.0 (https://seer.cancer.gov/seerstat/software/) (National Cancer Institute; National Institutes of Health, USA). Patients were eligible for inclusion, if having the evidence of the primary tumor location stated as ‘Pancreas’, the code of “ICD‑O‑3 Hist/behave, malignant” stated as ‘8490/3: Signet ring cell carcinoma’, the years of diagnosis from 2000 through 2019, and PSRCC being the first and only cancer diagnosis; Patients were excluded for missing any information such as radiotherapy records, surgery records, chemotherapy records, survival status, and time. Finally, A total of 588 patients were enrolled in the study. The histologic type was classified using the International Classification of Disease for Oncology, 3rd Edition (ICD-O-3), and the tumor stage categorized using Seer historic stage [14].

Statistical analysis

The main outcomes in our study were cancer-specific survival (CSS) and overall survival (OS), the specific definition of which referred to studies [13, 15, 16]. Data with continuous variables with nonnormal distributions were presented as M (P25, P75) and those with categorical variables as percentages. The variables were collected for analysis including diagnosis age, race, sex, location of the primary tumor, treatment information, survival time, and survival outcome of patients. The patient baseline characteristics were compared between the chemotherapy group and the non-chemotherapy group using Pearson’s chi-square test. Analyses on prognostic factors were performed using univariate and multivariate Cox analyses, least absolute shrinkage and selection operator (LASSO), and Random Survival Forest model, by which the hazard ratios (HRs) with 95% confidence intervals (CIs), nonzero coefficients, and scores of variable importance were calculated, respectively [13, 15]. Survival curves were generated by the Kaplan–Meier method, and differences in survival examined using the log-rank test. The possibility of multicollinearity was estimated using the variance inflation factors (VIFs). If those are less than 10, there was no overfitting problem. The clinical features with a statistical significance in univariate analysis or with clinical significance were selected for further analyses, but excluded if VIFs of which were greater than 10. Adjusted HRs and 95% CIs were calculated using multivariate Cox proportional hazard models. Subgroup analyses were used to further evaluate the prognostic value of chemotherapy in patients with different clinical features. Stata 16.0/MP and R (version 4.1.1, http://www.r-project.org.) software were used for statistical analysis. A two-sided p-value of less than 0.05 was considered statistically significant.

Ethics approval and consent to participate

The SEER was public-use data: informed consent was waived, and this is an observational study. The Research Ethics Committee of Mian Yang Hospital of Traditional Chinese Medicine has confirmed that no ethical approval is required.

Results

Demographic and clinical characteristics

A total of 588 patients meeting the study criteria were eventually selected, the median age of whom was 67(59, 75) years old. Of the 588 patients, 259 (44.05%) were female, and 329(55.95%) male; 267 (45.41%) underwent chemotherapy and 321(54.59%) did not. Patients’ demographics and tumor characteristics stratified by chemotherapy are summarized in Table 1. Using Pearson χ2 -test, significant differences between the two groups were observed concerning age (p< 0.001), tumor size (p = 0.021), marital status (p = 0.001), liver metastasis (p = 0.002), and radiotherapy (p< 0.001) (Table 1).

Table 1. Baseline characteristics of patients with PSRCC.

Characteristic Total (n = 588) Chemotherapy P
No (n = 321) Yes (n = 267)
Age, n (%), y < 0.001
    <60 155 (26.4) 62 (19.3) 93 (34.8)
    ≥60 433 (73.6) 259 (80.7) 174 (65.2)
Sex, n (%) 0.064
    Female 259 (44.0) 153 (47.7) 106 (39.7)
    Male 329 (56.0) 168 (52.3) 161 (60.3)
Race, n (%) 0.278
    White 486 (82.7) 258 (80.4) 228 (85.4)
    Black 60 (10.2) 37 (11.5) 23 (8.6)
    Other 42 (7.1) 26 (8.1) 16 (6.0)
Tumor size, n (%), cm 0.021
    ≤4cm 148 (25.2) 69 (21.5) 79 (29.6)
    >4cm 339 (57.7) 187 (58.3) 152 (56.9)
    Unknown 101 (17.2) 65 (20.2) 36 (13.5)
Tumor location, n (%) 0.178
    Head 282 (48.0) 148 (46.1) 134 (50.2)
    Body/tail 143 (24.3) 74 (23.1) 69 (25.8)
    Unknown 163 (27.7) 99 (30.8) 64 (24.0)
Marital status, n (%) 0.001
    Married 339 (57.7) 163 (50.8) 176 (65.9)
    Unmarried/divorce 225 (38.3) 142 (44.2) 83 (31.1)
    Unknown 24 (4.1) 16 (5.0) 8 (3.0)
Tumor stage, n (%) 0.603
    Localized/regional 147 (25.0) 75 (23.4) 72 (27.0)
    Distant 333 (56.6) 186 (57.9) 147 (55.1)
    Unknown 108 (18.4) 60 (18.7) 48 (18.0)
Liver metastasis, n (%) 0.002
    No 149 (25.3) 65 (20.2) 84 (31.5)
    Yes 117 (19.9) 60 (18.7) 57 (21.3)
    Unknown 322 (54.8) 196 (61.1) 126 (47.2)
Grade, n (%) 0.486
    I/II 33 (5.6) 15 (4.7) 18 (6.7)
    III/IV 234 (39.8) 132 (41.1) 102 (38.2)
    Unknown 321 (54.6) 174 (54.2) 147 (55.1)
Surgery, n (%) 0.112
    No 482 (82.0) 271 (84.4) 211 (79.0)
    Yes 106 (18.0) 50 (15.6) 56 (21.0)
Radiotherapy, n (%) < 0.001
    No 553 (94.0) 317 (98.8) 236 (88.4)
    Yes 35 (6.0) 4 (1.2) 31 (11.6)

Survival outcome analysis

The median follow-up was 3 (1,9) months. Of the 267patients in the chemotherapy group, 246 died (92.1%), including 233 tumor-related deaths (87.3%); Of the 321 patients in the non-chemotherapy group, 310 died (96.6%), including 294 tumor-related deaths (91.6%). The estimated 1-year OS of the chemotherapy group and the non-chemotherapy group were 31.2% and 13.4%, respectively and the estimated 1-year CSS were 32.4% and 14.0%, respectively. There were significant differences in OS and CSS between the two groups (all P < 0.05), suggesting chemotherapy could increase the OS and CSS in patients with PSRCC (Fig 1).

Fig 1.

Fig 1

OS (A) and CSS (B) curves of PSRCC patients.

Univariate and multivariate Cox regression model

To identify more independent prognostic factors for OS and CSS, the univariate and the multivariate Cox regression analysis were used. In the univariate Cox regression model, we found that age, tumor location, tumor size, marital status, tumor stage, grade, liver metastasis, radiotherapy, surgery, and chemotherapy were associated with the OS and the CSS (all P < 0.05) (Table 2).

Table 2. Univariate Cox regression analysis of CSS and OS in PSRCC patients.
Variables OS CSS
HR (95%CI) P HR (95%CI) P
Age, y
    <60 Reference Reference
    ≥60 1.32 [1.09, 1.59] 0.005 1.27 [1.05, 1.55] 0.015
Sex
    Female Reference Reference
    Male 1.02 [0.86, 1.21] 0.825 1.04 [0.87, 1.24] 0.661
Race
    White Reference Reference
    Black 1.06 [0.81, 1.40] 0.673 1.06 [0.80, 1.41] 0.665
    Other 1.02 [0.73, 1.42] 0.893 1.03 [0.73, 1.44] 0.879
Tumor location
    Head Reference Reference
    Body/tail 1.29 [1.05, 1.58] 0.017 1.28 [1.04, 1.58] 0.022
    Unknown 1.80 [1.47, 2.20] <0.001
Tumor size, cm
    ≤4cm Reference Reference
    >4cm 1.33 [1.09, 1.62] 0.005 1.34 [1.09, 1.65] 0.005
    Unknown 1.94 [1.49, 2.51] <0.001 1.93 [1.48, 2.52] <0.001
Marital status
    Married Reference Reference
    Unmarried/divorce 1.28 [1.08, 1.53] 0.005 1.30 [1.08, 1.55] 0.004
    Unknown 1.30 [0.85, 1.98] 0.227 1.24 [0.80, 1.93] 0.341
Tumor stage
    Localized/regional Reference Reference
    Distant 2.28 [1.85, 2.80] <0.001 2.31 [1.86, 2.85] <0.001
    Unknown 1.63 [1.24, 2.13] <0.001 1.61 [1.22, 2.13] 0.001
Grade
    I/II Reference Reference
    III/IV 1.86 [1.25, 2.76] 0.002 2.11 [1.37, 3.25] 0.001
    Unknown 2.67 [1.80, 3.97] <0.001 2.99 [1.94, 4.60] <0.001
Liver metastasis
    No Reference Reference
    Yes 1.78 [1.38, 2.30] <0.001 1.90 [1.46, 2.47] <0.001
    Unknown 1.56 [1.27, 1.92] <0.001 1.63 [1.32, 2.02] <0.001
Radiotherapy
    No Reference Reference
    Yes 0.34 [0.23, 0.49] <0.001 0.33 [0.22, 0.48] <0.001
Surgery
    No Reference Reference
    Yes 0.31 [0.24, 0.39] <0.001 0.30 [0.23, 0.39] <0.001
Chemotherapy
    No Reference Reference
    Yes 0.41 [0.34, 0.49] <0.001 0.41 [0.34, 0.49] <0.001

Further, the aforementioned variables were analyzed in a multivariate Cox regression model, to identify the independent prognostic factors for OS and CSS. The analysis shows that age, tumor location, marital status, tumor stage, grade, liver metastasis, surgery, and chemotherapy were associated with the OS and the CSS (all P < 0.05). Meanwhile, chemotherapy significantly improved the OS (HR = 0.34, 95% CI = 0.28 to 0.41, P <0.001) and CSS (HR = 0.33, 95% CI = 0.27 to 0.41, P <0.001), after adjusting for age, tumor location, marital status, tumor stage, grade, liver metastasis, and surgery. The details are shown in Fig 2.

Fig 2.

Fig 2

The forest plots for multivariate Cox regression analysis of OS (A) and CSS (B) in patients with PSRCC. VIF = variance inflation factor.

LASSO regression model

LASSO regression known to be able to remove unimportant variables via the regression coefficients penalizing the size of the parameters has been extended and broadly applied to the Cox proportional hazard regression model for survival analysis [17]. The coefficient estimates can be shrunk toward zero, with the degree of shrinkage dependent on an additional parameter, λ (Fig 3A and 3C). To determine the optimal values for λ, 10-fold cross-validation was used, and we chose λ via the1-SE criteria [18]. Finally, a λ value (for OS) of 0.2, with log (λ), -1.6, and a λ value (for CSS) of 0.19, with log (λ), -1.6 was chosen (Fig 3B and 3D). The variables with nonzero coefficients including chemotherapy (β = -0.24118), surgery (β = -0.52625), and tumor stage (β = 0.00027) were independent influencing factors for OS and chemotherapy (β = -0.248), surgery (β = -0.537) and tumor stage (β = 0.013) for CSS, showed by the results of the LASSO regression model.

Fig 3.

Fig 3

Feature selection based on LASSO regression (A and B for OS; C and D for CSS). LASSO coefficient profiles of the candidate variables, and a coefficient profile plot was produced against the log (λ) sequence; With the increment of the log (λ), the coefficient estimates shrink toward zero (A, C). tuning parameter (λ) selection in the LASSO model used 10-fold cross-validation via the 1-SE criteria, and the C-index curve was plotted versus log(λ); a λ value (for OS) of 0.2, with log (λ), -1.6 and a λ value (for CSS) of 0.19, with log (λ), -1.6 was chosen (blue dash line in B, D).

Random Survival Forest model

Random Survival Forest model, a machine learning algorithm with high robustness and without the restriction of Proportional Hazards Assumption, can prevent over-fitting problems via two random sampling processes. Here, we calculated scores of variable importance for OS and CSS, using the Random Survival Forest model. The results also indicated chemotherapy was an independent influencing factor for OS and CSS, with an importance score of 0.053 and 0.055, respectively (Fig 4).

Fig 4.

Fig 4

Scores of variable importance for OS (A) and CSS (B) using Random Survival Forest model.

Survival analysis for subgroups

Subgroup analyses using the Cox model were conducted to further determine the effect of chemotherapy for OS and CSS in patients with different features. we found that chemotherapy increased the OS and CSS in all subgroups. The results of the analyses are shown in Fig 5.

Fig 5.

Fig 5

The forest plots of the influence of chemotherapy on survival in different subgroups (A for OS and B for CSS).

Discussion

As a subtype of pancreatic ductal adenocarcinoma, PSRCC is very rare [8]. To our best knowledge, only 21 cases were reported in the literature [8, 19–35]. The value of chemotherapy was still unclear for the lack of high-quality clinical evidence and large samples of multicenter clinical studies. For this purpose, we used real-world data from the SEER database to investigate the value of chemotherapy for PSRCC patients. Previous studies have confirmed that chemotherapy has well-established survival benefits for patients with pancreatic cancer [36–39]. Yet, the value of chemotherapy for PSRCC remains unclear.

In the present study based on the largest sample, we showed for the first time in PSRCC that chemotherapy was significantly associated with OS (HR = 0.33, 95% CI = 0.27–0.4, P <0.001) and CSS (HR = 0.32, 95% CI = 0.26–0.39, P <0.001), that an independent factor influencing prognosis, and that could independently improve the OS and the CSS.

Radojkovic et al. [24] presented a PSRCC patient with a good response to neoadjuvant chemotherapy (after a 3-month neoadjuvant chemotherapy course with gemcitabine alone, the tumor in the head of the pancreas with 4.5 cm in the largest diameter regressed to 1.5 cm in largest diameter). Our findings, to some extent, were further confirmed by Radojkovic et al. [24]. Similar to our study, a recent study indicated that chemotherapy enhanced the CSS (HR = 0.549, 95% CI = 0.413–0.728, P <0.001) for bladder signet ring cell carcinoma [14], further corroborating our findings. In addition, Hugen et al. [40] also found that adjuvant chemotherapy is associated with improving survival in colorectal signet-ring cell carcinoma patients. Furthermore, in the study by Cai et al. [41], it was also found that chemotherapy was significantly associated with OS (HR = 0.54, 95% CI = 0.45–0.65, P <0.0001). The studies by Hugen et al. [40] and Cai et al. [41] were consistent with our findings.

Yet, in contrast to the findings described above, gastric signet ring cell carcinoma and colorectal signet ring cell carcinoma were not sensitive to chemotherapy in some studies [42–45], which may be explained by the different chemotherapy protocols and the unique biological behavior. For gastric signet ring cell carcinoma, previous chemotherapy protocol was largely based on treatment with 5-fluorouracil and platinum-based therapies, but the subsequent study suggests that gastric signet ring cell carcinoma may be uniquely chemosensitive to taxane-based therapy [46]. Furthermore, Thymidylate Synthase, the key enzyme for DNA synthesis pathways, is inhibited by 5-Fluorouracil. A study by Cabibi et al. [43] showed that colorectal signet ring cell carcinoma was negative for thymidylate synthase, and it may be one of the reasons for the insensitivity to chemotherapy.

The following limitations of this study should be considered. First, there was selection bias in this study, for being a retrospective analysis [14]. Second, due to the limitations of the SEER database, the concrete chemotherapy regimen and the details of local regional recurrence data were not available, to impact the survival. Third, as an important factor for clinical decision-making and survival, the performance status of each patient was not provided in the SEER database. Our study has several strengths. First, we independently used univariate and multivariate Cox regression, LASSO, and Random Survival Forest model to analyze the prognostic factors for survival and also used subgroup analysis to adjust all other variables affecting the prognosis, making our conclusions more reliable and stable. Second, in comparison to a single institution, the SEER database has access to a much larger cohort of patients. To the best of our knowledge, this study included the largest sample for evaluating the value of chemotherapy in patients with PSRCC to date. Third, our study included 588 patients with 566 deaths for OS and 527 deaths for CSS. The large sample size and number of deaths provided sufficient power for the analyses.

In conclusion, Patients with PSRCC can benefit from chemotherapy, to be recommended for patients with PSRCC.

Supporting information

S1 Table. The minimal data.

(XLSX)

pone.0302685.s001.xlsx (42.5KB, xlsx)

Acknowledgments

We thank the open access to the database from SEER.

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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Decision Letter 0

Filomena de Nigris

5 Mar 2024

PONE-D-24-04991Effect of chemotherapy on prognosis in patients with primary pancreatic signet ring cell carcinoma: A large real-world study based on machine learningPLOS ONE

Dear Dr. Huang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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PLOS ONE

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Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript is well presented, the topics well described. The tables and graphs are clear and sufficient. Only a few aspects would need to be revised by the authors:

• The work has no innovative features. Authors are requested to emphasize the new aspects considered in comparison with the following work: Nie, D., Lan, Q., Huang, Y. et al. Epidemiology and prognostic analysis of patients with pancreatic signet ring cell carcinoma: a population-based study. BMC Gastroenterol 22, 458 (2022). 10.1186/s12876-022-02543-z

• Authors should specify how they intend to overcome the bias of their study in the discussion.

• Authors should review the bibliography (ex: 4-5)

Reviewer #2: In the paper by Yunshen He et al., the role of chemotherapy as a prognostic factor of primary pancreatic singet ring cell carcinoma, a rare pancreatic ductal adenocarcinoma, is investigated through a statistical analysis. the paper is well written but:

- The introduction is too short and does not delve into any topic about pancretic cancer or PSRCC. It is not satisfactory for a student reader and very poor for an academic reader.

- Statistical analysis does not make any histological classification - Statistical analysis does not mention the different treatment groups, but in general chemotherapy it is not easy to understand if there is an effect of radiotherapy. The author should be able to take the effect of radiotherapy or a particular radiotherapy protocol in combination or individually.

Although the idea of the proposed analysis may be interesting, it is presented in a very superficial way, leaving unresolved many aspects about the variability of treatments, staging, etc.

**********

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Reviewer #1: No

Reviewer #2: No

**********

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PLoS One. 2024 May 13;19(5):e0302685. doi: 10.1371/journal.pone.0302685.r002

Author response to Decision Letter 0


22 Mar 2024

23th Mar, 2024

PONE-D-24-04991

Effect of chemotherapy on prognosis in patients with primary pancreatic signet ring cell carcinoma: A large real-world study based on machine learning.

Dear editors,

Thank you for your thoughtful review of our manuscript and the helpful comments from the reviewers. We agree with the reviewers’ suggestions. Here below a point-by-point reply to the comments. Major changes are marked in the revised manuscript. Hopefully you will find the revised manuscript improved and suitable for publication in PLOS ONE.

Reviewer 1

Q1:

The manuscript is well presented, the topics well described. The tables and graphs are clear and sufficient. Only a few aspects would need to be revised by the authors: The work has no innovative features. Authors are requested to emphasize the new aspects considered in comparison with the following work: Nie, D., Lan, Q., Huang, Y. et al. Epidemiology and prognostic analysis of patients with pancreatic signet ring cell carcinoma: a population-based study. BMC Gastroenterol 22, 458 (2022). 10.1186/s12876-022-02543-z; Authors should specify how they intend to overcome the bias of their study in the discussion.

Response:

We have meticulously reviewed the study by Nie et al., which centers on investigating the epidemiology of PSRCC. However, the content regarding prognostic analysis is relatively limited, and it does not specifically target the analysis of the value of chemotherapy. Furthermore, the outcome measures in this article are limited to Overall Survival (OS) only. In addition, the baseline characteristics of patients are not comprehensively presented in the comparison between chemotherapy and non-chemotherapy groups. In contrast, in this study, we aimed to specially investigate the prognostic value of chemotherapy in PSRCC. The patients’ demographics and tumor characteristics stratified by chemotherapy are detailedly summarized in Table 1. Also, the main outcomes in this study were cancer-specific survival (CSS) and OS, which enhances the reliability of the results. Further, we independently used univariate and multivariate Cox regression, LASSO, and Random Survival Forest model to analyze the prognostic factors for survival and also used subgroup analysis to adjust all other variables affecting the prognosis, making our conclusions more reliable and stable.

Notably, in addition to the aforementioned aspects, we have also utilized machine learning algorithms to optimize the methodology.

Q2:

Authors should review the bibliography (ex: 4-5).

Response:

We have meticulously reviewed all the references in the full manuscript and confirmed their accuracy. For references 4 and 5, we have downloaded the PDF documents and uploaded them as supplementary materials.

Reviewer 2

Q1:

The introduction is too short and does not delve into any topic about pancretic cancer or PSRCC. It is not satisfactory for a student reader and very poor for an academic reader.

Response:

We have made relevant additions and revisions to the introduction section.

Q2:

Statistical analysis does not make any histological classification

Response:

PSRCC is an extremely rare histologic variant of pancreatic cancers with the code of “ICD‑O‑3 Hist/behave, malignant” stated as ‘8490/3: Signet ring cell carcinoma’. In this study, we exclusively focus on a specific histological type of pancreatic cancers to investigate the influence of chemotherapy on prognosis. Consequently, the statistical analysis does not involve any other histological classification.

Q3:

Statistical analysis does not mention the different treatment groups, but in general chemotherapy it is not easy to understand if there is an effect of radiotherapy. The author should be able to take the effect of radiotherapy or a particular radiotherapy protocol in combination or individually. Although the idea of the proposed analysis may be interesting, it is presented in a very superficial way, leaving unresolved many aspects about the variability of treatments, staging, etc.

Response:

In our study, we not only utilized the standard univariate and multivariate Cox regression models and LASSO regression model for prognostic variable analysis but also employed the Random Survival Forest model and Survival Analysis for Subgroups. The Random Survival Forest model is advantageous as it lacks the constraint of the Proportional Hazards Assumption and prevents overfitting through its dual random sampling processes. On the other hand, Survival Analysis for Subgroups allows for the observation of chemotherapy's impact on patient prognosis at various subgroup levels after adjusting for the influence of other variables. This comprehensive statistical approach enhances the robustness of our findings and provides a nuanced understanding of how chemotherapy may affect outcomes within specific patient populations. ( Fig 5)

Attachment

Submitted filename: A rebuttal letter.docx

pone.0302685.s002.docx (18.7KB, docx)

Decision Letter 1

Filomena de Nigris

9 Apr 2024

Effect of chemotherapy on prognosis in patients with primary pancreatic signet ring cell carcinoma: A large real-world study based on machine learning

PONE-D-24-04991R1

Dear Dr Huang

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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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Filomena de Nigris, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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 #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have responded clearly and comprehensively to the comments raised in the first revision, therefore the manuscript is suitable for publication

Reviewer #2: the author's answers are exhaustive within the scope of the paper's objective even if some remain perplexed about the validity of the paper's idea.

**********

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.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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 #1: No

Reviewer #2: No

**********

Acceptance letter

Filomena de Nigris

30 Apr 2024

PONE-D-24-04991R1

PLOS ONE

Dear Dr. Huang,

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

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

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

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Prof. Filomena de Nigris

Academic Editor

PLOS ONE

Associated Data

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

    Supplementary Materials

    S1 Table. The minimal data.

    (XLSX)

    pone.0302685.s001.xlsx (42.5KB, xlsx)
    Attachment

    Submitted filename: A rebuttal letter.docx

    pone.0302685.s002.docx (18.7KB, docx)

    Data Availability Statement

    “All relevant data are within the paper and its supporting information files.”


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