A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study

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This study aimed to develop and validate a risk score for early prediction of VTE in these patients. Methods: Four hundred and one patients with lung cancer from three pulmonology departments hospitalized between January 2011 and December 2021 were retrospectively assessed. The population was divided into two groups: a Development Group (182 patients) and a validation group (199 patients). In the development group, the risk score system was developed, via univariate and multivariate analyses, based on demographic and clinicopathological variables; it was then validated in the validation group. Results: The incidence of VTE was 26.8% in the development group. It was 25.8%, and 27.6% in the internal and external validation groups, respectively. Hemoglobin level <10g/l, metastasis, histological type poorly or undifferentiated non-small cell carcinoma, and active smoking were the items of the risk score system. This score allowed proper stratification of patients with either high or low risk of VTE in the development group (c statistic =0.703). The patients in the development group were classified into 3 risk groups: low risk (scores 0-1), moderate risk (scores 2-3), and high risk (scores 4-5). When validated in the validation group, there was a moderate loss of predictive power of the score (c statistic=0.641), but the categorization of the patients by the score remained clinically useful. Conclusions: This risk score requires prospective validation studies on a nationwide scale in order to use it as a valid tool for the prevention of VTE in lung cancer." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/12-1388/v2", "name": "A novel risk score for venous thromboembolism in lung cancer patients:..." } } ] } Home Browse A novel risk score for venous thromboembolism in lung cancer patients:... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Rouis H, Moussa C, mejri I et al. A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.12688/f1000research.138878.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Revised A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] Houda Rouis 1 , Chirine Moussa https://orcid.org/0000-0002-8123-9843 1 , Islem mejri 2 , [...] Soumaya Debbiche 1 , Nourchene Khalfallah 3 , Lenda Ben Hmida https://orcid.org/0000-0001-7752-0723 2 , Amel Khattab 1 , Zied Moetamri 2 , Mohamed Lamine Megdiche 3 , Hela Kamoun https://orcid.org/0000-0003-4431-846X 3 , Sonia Maâlej 1 Houda Rouis 1 , Chirine Moussa https://orcid.org/0000-0002-8123-9843 1 , [...] Islem mejri 2 , Soumaya Debbiche 1 , Nourchene Khalfallah 3 , Lenda Ben Hmida https://orcid.org/0000-0001-7752-0723 2 , Amel Khattab 1 , Zied Moetamri 2 , Mohamed Lamine Megdiche 3 , Hela Kamoun https://orcid.org/0000-0003-4431-846X 3 , Sonia Maâlej 1 PUBLISHED 18 Aug 2025 Author details Author details 1 Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Ariana, Tunisia 2 pneumology, Military Hospital of Tunis, Tunis, 1008, Tunisia 3 Ibn Nafis, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Ariana, Tunisia Houda Rouis Roles: Conceptualization, Data Curation, Methodology, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Chirine Moussa Roles: Data Curation, Methodology, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Islem mejri Roles: Data Curation, Methodology, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Soumaya Debbiche Roles: Data Curation, Writing – Original Draft Preparation Nourchene Khalfallah Roles: Data Curation, Writing – Original Draft Preparation Lenda Ben Hmida Roles: Data Curation, Writing – Original Draft Preparation Amel Khattab Roles: Data Curation, Resources, Writing – Review & Editing Zied Moetamri Roles: Supervision, Validation, Visualization, Writing – Review & Editing Mohamed Lamine Megdiche Roles: Supervision, Validation, Visualization, Writing – Review & Editing Hela Kamoun Roles: Supervision, Validation, Visualization, Writing – Review & Editing Sonia Maâlej Roles: Supervision, Validation, Visualization, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Oncology gateway. Abstract Background: Venous thromboembolism (VTE) is a common and potentially fatal complication in patients with lung cancer. This study aimed to develop and validate a risk score for early prediction of VTE in these patients. Methods: Four hundred and one patients with lung cancer from three pulmonology departments hospitalized between January 2011 and December 2021 were retrospectively assessed. The population was divided into two groups: a Development Group (182 patients) and a validation group (199 patients). In the development group, the risk score system was developed, via univariate and multivariate analyses, based on demographic and clinicopathological variables; it was then validated in the validation group. Results: The incidence of VTE was 26.8% in the development group. It was 25.8%, and 27.6% in the internal and external validation groups, respectively. Hemoglobin level <10g/l, metastasis, histological type poorly or undifferentiated non-small cell carcinoma, and active smoking were the items of the risk score system. This score allowed proper stratification of patients with either high or low risk of VTE in the development group (c statistic =0.703). The patients in the development group were classified into 3 risk groups: low risk (scores 0-1), moderate risk (scores 2-3), and high risk (scores 4-5). When validated in the validation group, there was a moderate loss of predictive power of the score (c statistic=0.641), but the categorization of the patients by the score remained clinically useful. Conclusions: This risk score requires prospective validation studies on a nationwide scale in order to use it as a valid tool for the prevention of VTE in lung cancer. READ ALL READ LESS Keywords Lung cancer, Venous thromboembolism, risk score Corresponding Author(s) Chirine Moussa ( [email protected] ) Close Corresponding author: Chirine Moussa Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 Rouis H et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Rouis H, Moussa C, mejri I et al. A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.12688/f1000research.138878.2 ) First published: 20 Oct 2023, 12 :1388 ( https://doi.org/10.12688/f1000research.138878.1 ) Latest published: 18 Aug 2025, 12 :1388 ( https://doi.org/10.12688/f1000research.138878.2 ) Revised Amendments from Version 1 In response to the reviewers' and editors’ comments, several modifications have been made to improve the clarity and structure of the manuscript. First, we clarified the distinction between general chemotherapy and platinum-based chemotherapy, given the latter's established association with venous thromboembolism (VTE) risk and its inclusion in risk scores such as PROTECHT. This distinction was emphasized in the Methods and Discussion sections. Second, we have updated the Methodology section to better describe the variables included in the univariate and multivariate analyses, and we have provided justification for the inclusion threshold (p < 0.25) based on the purposeful selection method. Third, we revised the description of the statistical analysis to align with standard reporting practices. Additionally, the limitations of the study, previously mentioned in the Conclusion, have now been repositioned in the Discussion section to improve manuscript flow and comply with journal guidelines. Lastly, minor textual and formatting corrections were made throughout the manuscript for improved readability and consistency. In response to the reviewers' and editors’ comments, several modifications have been made to improve the clarity and structure of the manuscript. First, we clarified the distinction between general chemotherapy and platinum-based chemotherapy, given the latter's established association with venous thromboembolism (VTE) risk and its inclusion in risk scores such as PROTECHT. This distinction was emphasized in the Methods and Discussion sections. Second, we have updated the Methodology section to better describe the variables included in the univariate and multivariate analyses, and we have provided justification for the inclusion threshold (p < 0.25) based on the purposeful selection method. Third, we revised the description of the statistical analysis to align with standard reporting practices. Additionally, the limitations of the study, previously mentioned in the Conclusion, have now been repositioned in the Discussion section to improve manuscript flow and comply with journal guidelines. Lastly, minor textual and formatting corrections were made throughout the manuscript for improved readability and consistency. See the authors' detailed response to the review by Ping Wang See the authors' detailed response to the review by Georgia Gomatou READ REVIEWER RESPONSES Introduction Patients diagnosed with cancer are at a higher risk of developing venous thromboembolism (VTE) compared to the general population, with reported incidence rates ranging from 20% to 30%. 1 Among cancer types, lung cancer is particularly associated with thrombosis, with incidence rates ranging from 14% to 30%. 2 The risk of thrombosis is significantly increased in cancer patients, by 4 to 12 times higher compared to individuals without cancer, and further elevated to 6.5 to 23 times with the addition of chemotherapy or targeted therapy. 3 – 5 Various factors contribute to this increased risk, including patient-related factors such as advanced age, previous history of VTE, and obesity; tumor-related factors such as cancer type, stage, and aggressiveness; and treatment-related factors like surgery, radiation, or systemic anticancer. 1 , 6 The reported incidence of VTE in the literature varies, possibly due to differences in study design, selection of study participants, varying definitions of VTE, and the exclusion of patients with previous thrombosis from most clinical trials. 1 The correlation between cancer and venous thromboembolism (VTE) has been extensively established and is known to have deleterious effects on both morbidity and mortality among cancer patients. 5 VTE, including pulmonary embolism (PE) and deep vein thrombosis (DVT), as well as arterial thromboembolism, rank as the second most common cause of death in cancer patients. 1 Moreover, cancer patients with superficial vein thrombosis (SVT) face a high risk of death comparable to those with DVT. 6 Preventing VTE is an essential component of managing lung cancer patients to improve their prognosis. Therefore, several medical scoring systems have been developed to predict the risk of VTE, such as the Khorana, Caprini, Vienna CATS, PROTECHT, and COMPASS-CAT scores. 7 Nevertheless, these risk prediction scores have been developed with inherent limitations and have undergone limited external validation in lung cancer patients. Additionally, their applicability to the Tunisian population is restricted. Consequently, it is a priority to develop and validate a score specifically tailored to the Tunisian population. This will facilitate the guidance of prophylactic anticoagulation in patients at risk of VTE. Methods Sample size calculation Considering the objective of reducing the risk of VTE by 10% through the implementation of a VTE predictive score to guide prophylactic anticoagulation in lung cancer patients, it was determined that a sample size of 360 patients would be necessary to attain statistical significance (power: 0.8; alpha: 0.05), as calculated using a predictive formula. 8 Source of data We conducted a multicenter retrospective cohort study during the period between January 2011 and December 2021, involving the records of 410 patients who were diagnosed with lung cancer of all stages and who were hospitalized in the Department 1 or Ibn Néfis Department of Abderrahmane Mami Hospital of Ariana, or in the Pulmonary Department of the Principal Military Hospital of Tunis. Participants Ethics approval The study was approved by the ethics committee of Abderrahmane Mami Hospital under the approval number 27/2023. Written informed consent was collected from the patients. Anonymity was respected during data treatment. Inclusion criteria We enrolled all hospitalized patients whose diagnosis of primary lung cancer was histologically confirmed and who required hospitalization. Non-inclusion and exclusion criteria To ensure appropriate patient selection and data integrity, patients were either not included or excluded based on the following criteria: • Histologically unconfirmed primary lung cancer • Secondary pulmonary localizations • History of other malignancies • Acute phase of myocardial infarction • Acute phase of stroke • Medical records with insufficient or missing data Data collection Demographic and clinical data were collected at the time of hospital admission immediately following lung cancer diagnosis confirmation, before initiation of any anticancer therapy. The data collected included: demographic and clinicopathological data (age, gender, BMI, WHO status, smoking, hypertension, diabetes, dyslipidemia, coronary artery disease, heart failure, and surgical history), biological data (blood cell count (White blood cells, Hemoglobin, Platelets), C-reactive Protein (CRP), and creatinine), lung cancer data (histological type, TNM classification, length of follow-up, surgical treatment, chemotherapy, regimen of chemotherapy (platinum-based chemotherapy), and radiation), and VTE data (occurrence of PEor DVT, and the time to their onset). Access to treatments during the study period Although recent advances in lung cancer therapy have introduced immune checkpoint inhibitors and targeted agents, it is important to note that during the study period (spanning nearly ten years), access to these innovative treatments remained extremely limited in Tunisia. These therapies were only introduced into clinical practice within the last two years and were not available to most patients in the public healthcare system. As a result, all our patients were treated with conventional chemotherapy regimens, and none of the patients included in the VTE group had received immunotherapy or anti-angiogenic agents prior to the thromboembolic event. This ensured a relative homogeneity in treatment exposure across the cohort. Outcomes The event is defined as the occurrence of a VTE, which includes DVT, SVT, and/or PE. SVT is a thrombosis occurring in a superficial vein. It is usually caused by an inflammatory reaction in the wall of the thrombosed vein. The diagnosis is strongly suggested clinically and confirmed by Doppler ultrasound. DVT is characterized by the presence of a blood clot that completely or partially obstructs the blood flow in the deep venous system, most frequently in the lower limbs. The diagnosis is based on venous Doppler ultrasound. A PE occurs when a thrombus (blood clot) obstructs an artery in the lung, resulting in impaired blood flow. The diagnosis of PE is confirmed through a thoracic angio-scan. Statistical analysis Patient group allocation The patients were allocated to two groups: the development group (182 patients) and the validation group (199 patients). The development group was used to establish the scoring system, while the validation group was used to validate the developed score. Allocation was performed using numbers generated from the sequential medical record numbers, which were ranked and assigned via SPSS software. Statistical analysis and score development Data entry and analysis were conducted using IBM SPSS 23.0 software. Categorical variables were analyzed by calculating frequencies and percentages, and Pearson’s Chi-squared test was employed for frequency comparisons. The risk score was developed using a two-step process applied to the development cohort. First, a univariate analysis was performed to identify variables associated with preoperative venous thromboembolism (VTE). Variables with a significance level of p<0.25 were retained for multivariate analysis, following the purposeful selection method described by Bursac et al. (2008). 9 Second, a multivariate binary logistic regression was conducted to determine the independent predictors of VTE, with odds ratios (ORs) and 95% confidence intervals (CIs) calculated. Variables with p-values <0.05 were considered statistically significant and were included in the final predictive model. The weighting of these factors was determined by dividing the β coefficients by the absolute value of the smallest regression coefficient, rounding the result to the nearest integer. The sum of the weighted factors constituted the patient’s total risk score, which was calculated for both the development and validation groups to classify patients into risk groups. The cut-offs were fixed using the ROC curve analysis (receiver operating characteristic curve). Once a cut-off has been specified, the calculation of the predicted incidence allows a better classification of the patients into risk groups (low, moderate, and high). When our risk score was developed, its validation was done over two steps. The first step consists of the evaluation of the internal validity, which was done by studying the discrimination using the C statistic via the ROC curve analysis and the calibration via the Hosmer-Lemeshow test. The second step was based on the evaluation of the external validity. A total of 1000 bootstrap samples were selected from the database of the validation group to recalculate the discrimination and calibration of the risk model. For all statistical tests, the two-sided significance level was set at 0.5. Results Population characteristics and incidence of VTE A total of 381 patients were included in our study after the exclusion of 20 patients ( Figure 1 ). Thirty-nine patients had lung resection. Three hundred and nine patients (81.8% of cases) received first-line chemotherapy, which was combined with curative radiotherapy in 32.4% of cases. Figure 1. Flow chart of patient inclusion and exclusion. The incidence of VTE was 26.8% (102/381). It was similar in the development and validation groups (25.8% vs 27.6%; p=0.690). There was no significant difference in the incidence of pulmonary embolism (PE) (14.3% vs 14.6%; p=0.954), DVT (12.6% vs 12.5%; p=0.966), or SVT (1.1% vs 1.5%; p=0.731) between the 2 groups ( Figure 2 ). Figure 2. Incidence of VTE in patients followed for lung cancer. The main characteristics of the two databases are summarized in Table 1 . Table 1. Characteristics of patients in the development group and the validation group. Variables Development group n=182 Validation group n=199 χ 2 p Sex Female 30 (16.5) 21 (10.6) 2.884 0.089 Male 152 (83.5) 178 (89.4) Age (≥65 years) Yes 92 (50.5) 76 (38.2) 5.890 0.015 No 90 (49.5) 123 (61.8) BMI (≥25 kg/m 2 ) Yes 32 (17.6) 51 (25.6) 2.561 0.110 No 106 (58.2) 111 (55.8) WHO status (≥2) Yes 29 (15.9) 28 (14.1) 0.283 0.595 No 152 (83.5) 171 (85.9) TNM stage I-II 17 (9.3) 15 (7.5) 0.402 0.526 III-IV 165 (90.7) 184 (92.5) Lymph node status (≥N2) Yes 131 (72) 127 (69.8) 0.092 0.761 No 51 (28) 50 (37.9) Metastasis Yes 113 (62.1) 130 (65.3) 0.432 0.511 No 69 (37.9) 69 (34.7) Histological type Small-cell carcinoma 24 (13.2) 27 (13.6) 0.012 0.913 Poorly or undifferentiated 21 (11.5) 19 (9.5) 0.401 0.527 non-Small-cell carcinoma Squamous cell Carcinoma 48 (26.4) 46 (23.1) 0.543 0.461 Adenocarcinoma 84 (46.2) 95 (47.7) 0.096 0.757 Large cell carcinoma 3 (1.6) 7 (3.5) 1.300 0.254 Active smoking Yes 101 (55.5) 115 (57.8) 0.204 0.652 No 81 (45.5) 84 (42.2) Hypertension Yes 35 (19.2) 24 (12.1) 3.735 0.053 No 147 (80.8) 175 (87.9) Diabetes mellitus Yes 26 (14.3) 33 (16.6) 0.383 0.536 No 156 (85.7) 166 (83.4) Dyslipidemia Yes 9 (4.9) 9 (4.5) 0.038 0.846 No 173 (95.1) 190 (95.5) Coronaropathy Yes 17 (9.3) 14 (7) 0.676 0.411 No 165 (90.7) 185 (93) Cardiac failure Yes 6 (3.3) 5 (2.5) 0.208 0.648 No 176 (96.7) 195 (97.5) Renal failure Yes 3 (1.6) 1 (0.5) 1.201 0.273 No 179 (98.4) 198 (99.5) History of surgery Yes 43 (23.6) 52 (26.1) 0.352 0.553 No 139 (76.4) 146 (73.4) WBC (≥10 × 10 9 /l) Yes 70 (38.5) 102 (51.3) 6.781 0.009 No 112 (61.5) 97 (48.7) Hb (84 mmol/l) Yes 40 (22) 52 (26.1) 0.789 0.374 No 128 (70.3) 134 (67.3) C-Reactive protein (>5 mmol/l) Yes 134 (73.6) 153 (76.9) 0.021 0.886 No 22 (12.1) 24 (12.1) Tumor resection of lung cancer Yes 18 (10.4) 21 (10.6) 0.045 0.831 No 164 (90.1) 178 (89.4) Chemotherapy Yes 49 (81.9) 160 (80.4) 0.230 0.632 No 32 (18.5) 39 (19.6) Platinum based chemotherapy Yes 142 (78) 151 (75.9) 0.246 0.620 No 40 (22) 48 (24.1) Radiation Yes 55 (27.6) 54 (29.7) 0.198 0.656 No 142 (71.4) 126 (69.2) Identification of potential risk factors for VTE by Univariate analysis There is a statistically significant correlation between lymph node status (≥N2), presence of metastasis, active smoking, surgical history, hypertension, coronaropathy, and the occurrence of VTE. The univariate comparison for the identification of potential risk factors for VTE is detailed in Table 2 . Table 2. Comparison of variables between patients without and with VTE in the development group. Variables Without VTE n=135 With VTE n=47 χ 2 p Sex Female 25 (18.5) 5 (10.6) 1.573 0.210 Male 110 (83.5) 42 (89.4) Age (≥65 years) Yes 65 (48.1) 27 (57.4) 1.206 0.272 No 70 (51.9) 20 (42.6) BMI (≥25 kg/m 2 ) Yes 21 (15.6) 11 (23.4) 0.434 0.510 No 76 (56.3) 30 (63.8) WHO status (≥2) Yes 21 (15.6) 39 (83) 0.047 0.828 No 113 (83.7) 8 (17) TNM stage I-II 15 (11.1) 2 (4.3) 1.935 0.164 III-IV 120 (88.9) 45 (95.7) Lymph node status (≥N2) Yes 90 (66.7) 41 (87.2) No 45 (33.3) 6 (12.8) 7.312 0.007 Metastasis Yes 76 (56.3) 37 (78.8) 7.449 0.006 No 59 (43.7) 10 (21.3) Histological type Small-cell carcinoma 12 (8.9) 9 (19.1) 3.595 0.058 Poorly or undifferentiated 18 (13.3) 6 (12.8) 0.010 0.921 non-Small-cell carcinoma Squamous cell carcinoma 37 (27.4) 11 (23.4) 0.288 0.592 Adenocarcinoma 64 (47.4) 20 (42.6) 0.331 0.565 Large cell carcinoma 2 (1.5) 1 (2.1) 0.090 0.764 Active smoking Yes 69 (51.1) 35 (74.5) 9.236 0.002 No 66 (48.9) 12 (25.5) Hypertension Yes 34 (25.2) 46 (97.9) 11.933 0.001 No 101 (74.8) 1 (2.1) Diabetes mellitus Yes 21 (15.6) 5 (10.6) 0.688 0.407 No 114 (84.4) 42 (89.4) Dyslipidemia Yes 7 (5.2) 2 (95.7) 0.064 0.800 No 128 (94.8) 45 (4.3) Coronaropathy Yes 17 (12.6) 0 (0) 0.6528 0.011 No 118 (87.4) 47 (100) Cardiac failure Yes 6 (4.4) 0 (0) 2.160 0.142 No 129 (95.6) 47 (100) Renal failure Yes 3 (2.2) 0 (0) 1.062 0.303 No 132 (97.8) 47 (100) History of surgery Yes 98 (72.6) 6 (12.8) 4.142 0.042 No 37 (27.4) 41 (87.2) WBC (≥10 × 10 9 /l) Yes 52 (38.5) 18 (38.3) 0.004 0.951 No 82 (60.7) 29 (61.7) Hb (84 mmol/l) Yes 31 (23) 9 (19.1) 0.492 0.483 No 92 (68.1) 36 (76.6) C-Reactive protein (>5 mmol/l) Yes 94 (14.1) 40 (85.1) 2.488 0.115 No 19 (69.6) 3 (6.4) Tumor resection of lung cancer Yes 17 (12.6) 21 (10.6) 2.777 0.249 No 118 (87.4) 178 (89.4) Chemotherapy Yes 113 (83.7) 36 (23.4) 2.017 0.156 No 22 (16.3) 11 (76.6) Platinum-based chemotherapy Yes 110 (81.5) 32 (31.9) 3.649 0.056 No 25 (18.5) 15 (68.1) Radiation Yes 36 (26.7) 18 (38.3) 2.362 0.307 No 99 (73.3) 29 (61.7) Development of the predictive risk score system for VTE by multivariate analysis Determination of risk score system items Variables with a significance level of p<0.250 were entered into the binary logistic regression. A hemoglobin level <10 g/l, the presence of metastases, the histological type of poorly or undifferentiated NSCLC, and active smoking are the significant variables (p<0.05; therefore, they have been selected as the items of the score. Based on the weight of the different regression coefficients, we established a risk score system as follows ( Table 3 ): Table 3. Predictive factors for VTE determined from the development group by Multivariate analysis. Variables Score B Wald p OR, IC 95% Hemoglobin level <10 g/l +1 1.508 4.258 0.039 4.520 [1.079-18.937] Presence of metastasis +1 1.197 5.670 0.017 3.311 [1.236-8.871] Histological type poorly or undifferentiated NSCLC +2 1.875 6.390 0.011 6.522 [1.524-27.911] Active smoking +1 1.431 9.309 0.002 4.183 [1.668-10.488] The risk of VTE was significantly correlated with the risk score in the development group (Pearson contingency coefficient=26.757, p<10 -3 ). Determination of risk groups The cut-off of our VTE predictive score was identified via the ROC curve. Indeed, a total score <2 allows the classification of patients in the “low risk of VTE” group. The other risk classes were developed on the basis of the predicted incidence of VTE. As a result, patients were classified into 3 risk groups ( Table 4 ): “low risk” (score 0-1 [predicted incidence 43%, n=5]). Table 4. Classification of patients according to the predicted risk of the risk score and the actual incidence of VTE. Score Development group Validation group Predicted incidence Number of patients Actual incidence (%) Risk group PPV/NPV (%) Predicted incidence Number of patients Actual incidence (%) Risk group PPV/NPV (%) 0 4.7% 25 2 (8%) low risk (<29%, n=92) NA/87 Se=NA Sp=100% 10.1% 30 4 (13.33%) low risk (<29%, n=101) NA/82 Se=NA Sp=100% 1 18.1% 67 10 (14.9%) 21.4% 71 14 (19.71%) 2 38.8% 64 22 (34.4%) Moderate risk (29-43%, n=85) 48/82.9 Se=80% Sp=52.7% 37.33% 76 27 (35.5%) Moderate risk (29-43%, n=86) 80/63.3 Se=12.1% Sp=98% 3 53.1% 21 8 (38.1%) 40% 10 6 (60%) 4 83.9% 5 5 (100%) High risk (>43%, n=5) 100/NA Se=100% Sp=NA 35.47% 11 4 (36.3%) High risk (>43%, n=12) NA/66.7 Se=NA Sp=100 5 0 % 0 0 (0%) 48.7% 1 0 (0%) The incidence of VTE according to the 3 risk classes in the development group and in the validation group is detailed in Figure 3 . Figure 3. Distribution of VTE according to the 3 risk classes between the development group and the validation group. The percentages of VTE in “low-risk” and “moderate-risk” patients are similar between the development and validation groups (low-risk: 13% vs 17.8%, moderate-risk: 35.3% vs 38.4%; respectively). In contrast, the percentage of VTE in “high-risk” patients is much higher in the development group compared to the patients in the validation group (100% vs 36.3%, p=0.012) Validation of VTE predictive score Internal validation In the development group, the risk score system has good discrimination. It can distinguish “high-risk” from “low-risk” VTE patients (c statistic=0.703 [0.618-0.789], ( Figure 4 A)). This prediction model also showed good calibration according to the Hosmer-Lemeshow test (χ 2 =2.381, p=0.882). Figure 4. (A) ROC curve of VTE prediction model using the development group. (B) ROC curve of VTE prediction model using the validation group and after applying the bootstrap method (1000 samples). External validation The risk score system shows low discrimination in the validation group (c-statistics=0.641 [0.557-0.726], ( Figure 4 )). However, despite being poorly discriminating, it was well calibrated according to the Hosmer-Lemeshow test (χ 2 = 6.250; p=0.396). Considering the aforementioned classification, patients in the validation group were classified into 3 risk groups ( Table 4 ): “low risk” (score 0-1 [predicted incidence 43%, n=12). Discussion We created a novel prediction model to assess the risk of venous thromboembolism (VTE) in patients diagnosed with lung cancer in the development cohort. Subsequently, we conducted an external validation of the model using a separate validation cohort. Our study involved a total of 381 patients, and our findings indicated that the prevalence of VTE in lung cancer patients was 26.8%, surpassing the rates reported in previous studies. 10 – 12 The variability in the incidence of VTE is due to several risk factors. In our study, lymph node status (≥N2), presence of metastasis, active smoking, surgical history, hypertension, and absence of coronaropathy were correlated with the occurrence of VTE. However, in other Tunisian studies, TNM stage IV and non-small squamous carcinoma were associated with high VTE incidence. 10 , 11 Thus, to reduce the occurrence of VTE, it is imperative to identify and assess all possible risk factors while determining the appropriate prophylactic measures for these patients. Various predictive models have been suggested to anticipate VTE occurrence in individuals with lung cancer. These models have incorporated several factors based on existing literature, and it is important to consider biomarkers associated with thrombosis. 13 The Khorana risk score, a widely recognized predictive scoring system, categorizes cancer patients into distinct risk groups and identifies a high-risk group for thromboprophylaxis. It is considered the prevailing and valuable tool for predicting VTE in the cancer population. 13 , 14 The majority of factors included in various risk scoring systems have been incorporated into our risk score system. However, we did not include the D-dimer test, despite its significance, due to the limited number of observed values in our dataset. 14 and, most importantly, due to the unavailability of this test in our current practice. Furthermore, these aforementioned predictive risk scores were developed using data from patients diagnosed with various types of cancer, whereas our scoring system is specifically tailored to lung cancer patients. 14 Thus, lung cancer data were included in our score but not adopted in most models. Some of these variables were present in our definitive risk score (i.e., the presence of metastasis and histological type of poorly or undifferentiated NSCLC). In previous retrospective studies reported in the literature, adenocarcinoma has been identified as a strong predictor of VTE onset. 14 Blom et al. conducted a study involving 537 NSCLC patients to investigate thrombotic risk and observed a 20-fold higher risk of VTE compared to the general population. Among the patients, those with adenocarcinoma had a three-fold higher risk (incidence=66.7%) than those with squamous cell carcinoma of the lung (incidence=21.2%). 15 Similarly, in another cohort of 493 NSCLC patients, Tagalakis et al. reported a high incidence of DVT (13.6%). 16 However, in our study, we found that poorly or undifferentiated NSCLC was associated with a higher prevalence of VTE, while adenocarcinoma was not predictive of the occurrence of VTE. 14 Blom et al. 15 , 16 Body mass index (BMI), which is incorporated in both the Khorana score and Caprini VTE risk assessment, was integrated into our risk system. However, we used a lower cut-off (≥25 kg/m 2 ) possibly due to the prevalence of poor nutritional status among lung cancer patients. 5 , 17 The hemogram parameter (hemoglobin, platelets, and leukocytes) included in the other risk score models was used in our study. Patients with a hemoglobin level <10 g/l had a four-fold higher risk of VTE. Other biomarkers, namely CRP and creatinine, were also included in our system; these biomarkers were not used by most VTE risk models. A cohort study investigating VTE risk among 3159 patients with newly diagnosed solid tumors concluded that elevated CRP and creatinine levels were predictive of VTE. 18 Our scoring system incorporates cancer therapy and surgery as variables. Previous studies have demonstrated that cancer therapy, including chemotherapy, antiangiogenic therapy, and hormonal therapy, increases the risk of VTE. 19 – 22 Christensen et al. , after reviewing 19 studies involving 10,660 patients with primary lung cancer undergoing curative-intent operations, found that the risk of VTE appears to be highest during the early postoperative period, with a subsequent decrease in risk. 23 As mentioned earlier, since risk factors vary from one population to another, there is a need to develop a risk score system specific to our population, in order to assist healthcare practitioners in developing appropriate prophylactic strategies for patients at risk of developing VTE. After conducting a logistic regression analysis in our study, we identified four items that were included in our risk score system. To the best of our knowledge, this risk score represents the first attempt to predict the potential incidence of VTE specifically for Tunisian patients with lung cancer. The developed risk score suggests that the incidence of VTE is expected to increase exponentially. Scores below 2 were associated with a low risk of VTE, while scores of 4 or higher were associated with a high risk. The discriminant validity of this VTE score system was confirmed in the validation group, although there was a moderate decrease in predictive power. However, the classification of patients based on the score remained clinically meaningful. The notable variation in prognosis among the three risk groups should aid physicians in determining the appropriate therapeutic approach. Therefore, we strongly recommend thromboprophylaxis for Tunisian patients with moderate and high VTE risks. Despite its poor predictive discrimination, this score presented several strengths. Firstly, to our knowledge, it is the first risk prediction model that included the occurrence of SVT as a predictable event. In fact, our decision to add SVT among outcomes was not arbitrary but based on several studies. A recent study conducted in 2022 highlighted the significance of SVT as a condition and revealed that patients with cancer and SVT are at an increased risk of thromboembolic complications. 24 In addition, Galanaud et al. suggested that cancer patients with SVT exhibit a poor prognosis, comparable to those with cancer-related DVT, with a heightened risk of recurrence of DVT-PE. Secondly, we believe that this score can be applied to other populations whose characteristics are quite similar to those of our Tunisian population and with poor means on board, especially in underdeveloped countries. Nevertheless, it is essential to perform external validation of this score using data from diverse populations in order to ensure its generalizability and reliability. The present study has several limitations that should be acknowledged. First, this study was based on 381 patients from three tertiary centers in northern Tunisia. Given the limited sample size, it is important to note that our patients may not adequately represent the diversity of our population. Secondly, we did not conduct an assessment of the reproducibility of our risk score in the prospective validation cohort. Thirdly, it is important to consider that personal and family history of VTE, as well as the use of anticoagulant or antiplatelet treatment at the time of lung cancer diagnosis, could potentially impact our findings. Finally, it should be noted that the cut-off values for the potential VTE variables included in our risk model were determined based on clinical experience or existing literature, rather than individualized threshold values determined by ROC curve analysis. We have tried to respond to a need specific to the characteristics of our country where the economic crisis makes it very difficult to provide care according to international standards. Our score contains simple items available to any Tunisian practitioner. The collection of the four items is straightforward: smoking history can be obtained through an interview, a complete blood count (CBC) is a readily available test in Tunisia, even in primary care settings, determining the histological type, and conducting staging assessments are commonly practiced. Conclusion In conclusion, the frequency of VTE in this study was high, at 26.8%. A predictive score for VTE was developed and validated by including epidemiological, clinical, and biological data. This score, despite its low discrimination, has a good positive and negative predictive value for a moderate risk of VTE. 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Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 20 Oct 2023 ADD YOUR COMMENT Comment Author details Author details 1 Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Ariana, Tunisia 2 pneumology, Military Hospital of Tunis, Tunis, 1008, Tunisia 3 Ibn Nafis, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Ariana, Tunisia Houda Rouis Roles: Conceptualization, Data Curation, Methodology, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Chirine Moussa Roles: Data Curation, Methodology, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Islem mejri Roles: Data Curation, Methodology, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Soumaya Debbiche Roles: Data Curation, Writing – Original Draft Preparation Nourchene Khalfallah Roles: Data Curation, Writing – Original Draft Preparation Lenda Ben Hmida Roles: Data Curation, Writing – Original Draft Preparation Amel Khattab Roles: Data Curation, Resources, Writing – Review & Editing Zied Moetamri Roles: Supervision, Validation, Visualization, Writing – Review & Editing Mohamed Lamine Megdiche Roles: Supervision, Validation, Visualization, Writing – Review & Editing Hela Kamoun Roles: Supervision, Validation, Visualization, Writing – Review & Editing Sonia Maâlej Roles: Supervision, Validation, Visualization, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (2) version 2 Revised Published: 18 Aug 2025, 12:1388 https://doi.org/10.12688/f1000research.138878.2 version 1 Published: 20 Oct 2023, 12:1388 https://doi.org/10.12688/f1000research.138878.1 Copyright © 2025 Rouis H et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Rouis H, Moussa C, mejri I et al. A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.12688/f1000research.138878.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 18 Aug 2025 Revised Views 0 Cite How to cite this report: Vasse M. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.186248.r455484 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v2#referee-response-455484 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Feb 2026 Marc Vasse , Université Paris-Saclay, Foch Hospital, Suresnes, France Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.186248.r455484 In this paper, the authors describe a new score to identify the thrombotic risk in lung cancer patients treated by "classical chemotherapy" used in low-to-middle-income countries. 1) The introduction is too long and bibliography is not relevant. ... Continue reading READ ALL In this paper, the authors describe a new score to identify the thrombotic risk in lung cancer patients treated by "classical chemotherapy" used in low-to-middle-income countries. 1) The introduction is too long and bibliography is not relevant. The frequency of thrombosis in lung cancer patients is not so high (20 to 30 %) as indicated, and the reference 1 applies to patients treated by check point inhibitors, that is not the case of the patients of this study. 2) I am surprised that patients are divided (fig 1) as only PE. No patients had both deep venous thrombosis and pulmonary embolism? 3) All cases of VTE are indicated as 102. Surprisingly, the sum of "only PE" + "only DVT " + only SVT is 108. 4) The authors indicate in the discussion that their score as a poor predictive value. Usually, despite a poor discriminating capacity in lung cancer patients, the Khorana score (KS) is used. A comparison of the Khorana score with this new score could be interesting. In addition, in lung cancer, KS is predictive of mortality (PMID 29806470). Is your score predictive of the mortality? Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests: I am currently working to identify new thrombotic risk factors in patients with lung cancer Reviewer Expertise: Coagulation, cancer associated thrombosis I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Vasse M. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.186248.r455484 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v2#referee-response-455484 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Gomatou G. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.186248.r406432 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v2#referee-response-406432 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 23 Aug 2025 Georgia Gomatou , Oncology Unit, Third Department of Medicine, “Sotiria” General Hospital for Diseases of the Chest, National and Kapodistrian University of Athens, Athens, Greece; National and Kapodistrian University of Athens School of Medicine, Athens, Attica, Greece Approved VIEWS 0 https://doi.org/10.5256/f1000research.186248.r406432 The authors have successfully incorporated ... Continue reading READ ALL The authors have successfully incorporated the reviewers' suggestions. No further comments. Competing Interests: No competing interests were disclosed. Reviewer Expertise: Medical Oncology, Thoracic Oncology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Gomatou G. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.186248.r406432 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v2#referee-response-406432 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 20 Oct 2023 Views 0 Cite How to cite this report: Gomatou G. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.152109.r335912 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v1#referee-response-335912 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 06 Nov 2024 Georgia Gomatou , Oncology Unit, Third Department of Medicine, “Sotiria” General Hospital for Diseases of the Chest, National and Kapodistrian University of Athens, Athens, Greece; National and Kapodistrian University of Athens School of Medicine, Athens, Attica, Greece Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.152109.r335912 This is an original study describing a prediction score of VTE in patients with lung cancer. In general, the manuscript is well-written and the methods and results are clearly presented. My suggestions in order to improve the paper: 1. ... Continue reading READ ALL This is an original study describing a prediction score of VTE in patients with lung cancer. In general, the manuscript is well-written and the methods and results are clearly presented. My suggestions in order to improve the paper: 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Medical Oncology, Thoracic Oncology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Gomatou G. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.152109.r335912 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v1#referee-response-335912 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 05 Sep 2025 CHIRINE MOUSSA , Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Tunisia 05 Sep 2025 Author Response 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and ... Continue reading 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and exclusion criteria. In our protocol, we initially presented them separately to reflect the different stages of patient selection: non-inclusion criteria correspond to conditions preventing initial eligibility (e.g., lack of histological confirmation), while exclusion criteria relate to factors identified after preliminary assessment (e.g., comorbidities, acute events, or unusable records). However, to improve clarity and according to your suggestion, we are happy to combine both into a single section titled “Non-inclusion and exclusion criteria” for simplicity and better readability. Proposed combined criteria: Histologically unconfirmed bronchopulmonary carcinoma (BPC) Secondary pulmonary localizations History of: • Other neoplasms • Acute phase of myocardial infarction (MI) • Acute phase of stroke Unusable medical records 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. Response to reviewer: Thank you for your valuable suggestion. We agree that discussing the study’s limitations is more appropriate in the Discussion section. We confirm that these limitations are already addressed within a dedicated paragraph of the Discussion. Accordingly, we will remove the sentence referring to the limitations from the Conclusions section to avoid redundancy and improve the overall clarity of the manuscript. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Response to the reviewer: Thank you for your valuable comment regarding the use of the term “randomization” in Figure 1. We acknowledge that the allocation process used in our study was based on generating “random” numbers from the sequence of patients’ medical record numbers. This method does not constitute a strict randomization procedure as per clinical trial standards, since medical record numbers are assigned sequentially and may introduce allocation bias. Therefore, to avoid any misunderstanding, we have removed the term “randomization” from Figure 1 and replaced it with “allocation” or a similar neutral term that better reflects the actual process. We appreciate your careful review and hope this clarifies the method used. 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and exclusion criteria. In our protocol, we initially presented them separately to reflect the different stages of patient selection: non-inclusion criteria correspond to conditions preventing initial eligibility (e.g., lack of histological confirmation), while exclusion criteria relate to factors identified after preliminary assessment (e.g., comorbidities, acute events, or unusable records). However, to improve clarity and according to your suggestion, we are happy to combine both into a single section titled “Non-inclusion and exclusion criteria” for simplicity and better readability. Proposed combined criteria: Histologically unconfirmed bronchopulmonary carcinoma (BPC) Secondary pulmonary localizations History of: • Other neoplasms • Acute phase of myocardial infarction (MI) • Acute phase of stroke Unusable medical records 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. Response to reviewer: Thank you for your valuable suggestion. We agree that discussing the study’s limitations is more appropriate in the Discussion section. We confirm that these limitations are already addressed within a dedicated paragraph of the Discussion. Accordingly, we will remove the sentence referring to the limitations from the Conclusions section to avoid redundancy and improve the overall clarity of the manuscript. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Response to the reviewer: Thank you for your valuable comment regarding the use of the term “randomization” in Figure 1. We acknowledge that the allocation process used in our study was based on generating “random” numbers from the sequence of patients’ medical record numbers. This method does not constitute a strict randomization procedure as per clinical trial standards, since medical record numbers are assigned sequentially and may introduce allocation bias. Therefore, to avoid any misunderstanding, we have removed the term “randomization” from Figure 1 and replaced it with “allocation” or a similar neutral term that better reflects the actual process. We appreciate your careful review and hope this clarifies the method used. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 05 Sep 2025 CHIRINE MOUSSA , Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Tunisia 05 Sep 2025 Author Response 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and ... Continue reading 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and exclusion criteria. In our protocol, we initially presented them separately to reflect the different stages of patient selection: non-inclusion criteria correspond to conditions preventing initial eligibility (e.g., lack of histological confirmation), while exclusion criteria relate to factors identified after preliminary assessment (e.g., comorbidities, acute events, or unusable records). However, to improve clarity and according to your suggestion, we are happy to combine both into a single section titled “Non-inclusion and exclusion criteria” for simplicity and better readability. Proposed combined criteria: Histologically unconfirmed bronchopulmonary carcinoma (BPC) Secondary pulmonary localizations History of: • Other neoplasms • Acute phase of myocardial infarction (MI) • Acute phase of stroke Unusable medical records 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. Response to reviewer: Thank you for your valuable suggestion. We agree that discussing the study’s limitations is more appropriate in the Discussion section. We confirm that these limitations are already addressed within a dedicated paragraph of the Discussion. Accordingly, we will remove the sentence referring to the limitations from the Conclusions section to avoid redundancy and improve the overall clarity of the manuscript. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Response to the reviewer: Thank you for your valuable comment regarding the use of the term “randomization” in Figure 1. We acknowledge that the allocation process used in our study was based on generating “random” numbers from the sequence of patients’ medical record numbers. This method does not constitute a strict randomization procedure as per clinical trial standards, since medical record numbers are assigned sequentially and may introduce allocation bias. Therefore, to avoid any misunderstanding, we have removed the term “randomization” from Figure 1 and replaced it with “allocation” or a similar neutral term that better reflects the actual process. We appreciate your careful review and hope this clarifies the method used. 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and exclusion criteria. In our protocol, we initially presented them separately to reflect the different stages of patient selection: non-inclusion criteria correspond to conditions preventing initial eligibility (e.g., lack of histological confirmation), while exclusion criteria relate to factors identified after preliminary assessment (e.g., comorbidities, acute events, or unusable records). However, to improve clarity and according to your suggestion, we are happy to combine both into a single section titled “Non-inclusion and exclusion criteria” for simplicity and better readability. Proposed combined criteria: Histologically unconfirmed bronchopulmonary carcinoma (BPC) Secondary pulmonary localizations History of: • Other neoplasms • Acute phase of myocardial infarction (MI) • Acute phase of stroke Unusable medical records 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. Response to reviewer: Thank you for your valuable suggestion. We agree that discussing the study’s limitations is more appropriate in the Discussion section. We confirm that these limitations are already addressed within a dedicated paragraph of the Discussion. Accordingly, we will remove the sentence referring to the limitations from the Conclusions section to avoid redundancy and improve the overall clarity of the manuscript. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Response to the reviewer: Thank you for your valuable comment regarding the use of the term “randomization” in Figure 1. We acknowledge that the allocation process used in our study was based on generating “random” numbers from the sequence of patients’ medical record numbers. This method does not constitute a strict randomization procedure as per clinical trial standards, since medical record numbers are assigned sequentially and may introduce allocation bias. Therefore, to avoid any misunderstanding, we have removed the term “randomization” from Figure 1 and replaced it with “allocation” or a similar neutral term that better reflects the actual process. We appreciate your careful review and hope this clarifies the method used. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Wang P. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.152109.r253369 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v1#referee-response-253369 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 15 May 2024 Ping Wang , The Fourth Hospital of Hebei Medical University, Shijiazhuang, China Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.152109.r253369 Many literatures have reported that the incidence rate of tumor with VTE is significantly higher than that of other diseases, and the incidence rate of lung cancer with VTE is higher. There are many studies on the risk factors of ... Continue reading READ ALL Many literatures have reported that the incidence rate of tumor with VTE is significantly higher than that of other diseases, and the incidence rate of lung cancer with VTE is higher. There are many studies on the risk factors of lung cancer combined with VTE, and many suggest that pathological types, stages, and other factors are related to the occurrence of VTE. This manuscript introduces several processes for establishing a VTE screening model, but some issues still need to be discussed. 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: Lung cancer and VTE, lung cancer and infection. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Wang P. Reviewer Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.152109.r253369 ) The direct URL for this report is: https://f1000research.com/articles/12-1388/v1#referee-response-253369 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 05 Sep 2025 CHIRINE MOUSSA , Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Tunisia 05 Sep 2025 Author Response 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients ... Continue reading 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? Response to reviewer Thank you for this relevant comment. We acknowledge that lung cancer management has significantly evolved over the past decade, particularly with the introduction of immune checkpoint inhibitors and targeted therapies. However, it is important to note that in Tunisia, a low-to-middle-income country, access to these innovative therapies remains extremely limited. Immunotherapy and targeted treatments have only been introduced into clinical practice in the past two years, and only a restricted number of molecules are currently available, due to their high cost and limited accessibility within the public health system. Consequently, throughout the study period, which spans nearly ten years, the vast majority of patients included were treated with conventional chemotherapy protocols. This contributes to the overall consistency of treatment regimens across the cohort. Moreover, at the time of inclusion, no patients in the VTE group had received immune checkpoint inhibitors or anti-angiogenic agents before the thromboembolic event. Thus, the potential impact of these newer therapies on the incidence of VTE was not a confounding factor in our analysis. We have now clarified this point in the revised manuscript. 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? Response to reviewer: Thank you for your insightful question. In our manuscript, we made a specific distinction between chemotherapy in general and platinum-based chemotherapy because of the well-established association between platinum compounds and increased risk of venous thromboembolism (VTE), particularly in lung cancer. This is why platinum-based chemotherapy is explicitly included in risk assessment tools such as the PROTECHT score. To clarify: “Chemotherapy” is a broad term that refers to any cytotoxic anticancer treatment, regardless of the drug class. “Platinum-based chemotherapy” refers specifically to regimens that include platinum compounds, such as cisplatin or carboplatin. Therefore, while platinum-based chemotherapy is indeed a subset of chemotherapy, we chose to identify it separately in our analysis due to its particular thrombotic profile and relevance to the pathophysiology of VTE in lung cancer patients. 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? Response to reviewer: Thank you for your question. For all enrolled patients, including those without VTE, the data on BMI, white blood cell count (WBC), hemoglobin (Hb), platelet count, creatinine, and C-reactive protein (CRP) were collected at the time of the first hospital admission, immediately after the confirmation of lung cancer diagnosis and prior to the initiation of any treatment, regardless of treatment type. This approach ensured uniformity in data collection and minimized the influence of treatment-related changes on baseline biological parameters. We have now clarified this point in the revised version of the manuscript. 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? Response to reviewer: Thank you for your valuable comment. The point allocation in Table 3 was not based solely on the statistical significance (p-values), but rather on the β coefficients obtained from multivariate logistic regression, which reflect the strength of association between each variable and the outcome (VTE occurrence). To construct the score, we applied a commonly used method in predictive model development, which involves: Dividing each β coefficient by the smallest absolute β coefficient in the model (used as a reference), Rounding the result to the nearest integer to assign the corresponding weight (score point). In our model, the smallest β coefficient was that of “Presence of metastases”, with a value of 1.197. We then applied the following calculations: Hemoglobin < 10 g/dL: 1.508 / 1.197 = 1.26, rounded to 1 point Presence of metastases: 1.197 / 1.197 = 1, rounded to 1 point Histological type difficult to classify (NSCLC): 1.875 / 1.197 = 1.57, rounded to 2 points Active smoking: 1.431 / 1.197 = 1.19, rounded to 1 point Therefore, even though active smoking had a low p-value, its β coefficient was not the highest among the predictors. The histological type variable had the largest coefficient and thus received the highest weight (2 points). This approach ensures that the scoring reflects the relative contribution of each predictor rather than just their individual statistical significance. 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Response to reviewer: Thank you for raising this important point. It is not uncommon for a variable to be non-significant in univariate analysis but become statistically significant in multivariate analysis. In our case, the hemoglobin level <10 g/dL had a p-value of 0 .228 in univariate analysis, yet became statistically significant (p = 0.039) in multivariate analysis. This phenomenon may be explained by the presence of confounding or interaction effects between variables. In univariate analysis, each variable is assessed in isolation, without adjusting for the influence of other potential covariates. In contrast, multivariate analysis accounts for the combined and adjusted effects of multiple predictors. Once other variables are included in the model — such as metastatic status, histological subtype, and smoking — the independent contribution of hemoglobin to VTE risk becomes more evident. Moreover, the decision to retain variables for multivariate modeling was based not only on statistical thresholds but also on epidemiological and clinical relevance. In line with the approach proposed by Bursac et al. (2008), we included variables with univariate p-values below 0.250, as this cutoff has been shown to reduce the risk of omitting important variables too early. This strategy was also recommended by the epidemiologists of our institution during the study design phase. References: ( Source: Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008 Dec 16;3:17. doi: 10.1186/1751-0473-3-17. PMID: 19087314; PMCID: PMC2633005. ) The reference was included as the ninth entry in the reference list; however, the remaining references were not updated accordingly. Therefore, although the univariate association between low hemoglobin and VTE was not statistically significant, we retained it in the multivariate model due to its known pathophysiological plausibility in cancer-associated thrombosis, and its potential contribution to a more robust predictive model. After adjustment for other covariates, the association became statistically significant. We have added a clarification to this effect in the revised Methods section. 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? Response to reviewer Thank you for this relevant comment. We acknowledge that lung cancer management has significantly evolved over the past decade, particularly with the introduction of immune checkpoint inhibitors and targeted therapies. However, it is important to note that in Tunisia, a low-to-middle-income country, access to these innovative therapies remains extremely limited. Immunotherapy and targeted treatments have only been introduced into clinical practice in the past two years, and only a restricted number of molecules are currently available, due to their high cost and limited accessibility within the public health system. Consequently, throughout the study period, which spans nearly ten years, the vast majority of patients included were treated with conventional chemotherapy protocols. This contributes to the overall consistency of treatment regimens across the cohort. Moreover, at the time of inclusion, no patients in the VTE group had received immune checkpoint inhibitors or anti-angiogenic agents before the thromboembolic event. Thus, the potential impact of these newer therapies on the incidence of VTE was not a confounding factor in our analysis. We have now clarified this point in the revised manuscript. 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? Response to reviewer: Thank you for your insightful question. In our manuscript, we made a specific distinction between chemotherapy in general and platinum-based chemotherapy because of the well-established association between platinum compounds and increased risk of venous thromboembolism (VTE), particularly in lung cancer. This is why platinum-based chemotherapy is explicitly included in risk assessment tools such as the PROTECHT score. To clarify: “Chemotherapy” is a broad term that refers to any cytotoxic anticancer treatment, regardless of the drug class. “Platinum-based chemotherapy” refers specifically to regimens that include platinum compounds, such as cisplatin or carboplatin. Therefore, while platinum-based chemotherapy is indeed a subset of chemotherapy, we chose to identify it separately in our analysis due to its particular thrombotic profile and relevance to the pathophysiology of VTE in lung cancer patients. 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? Response to reviewer: Thank you for your question. For all enrolled patients, including those without VTE, the data on BMI, white blood cell count (WBC), hemoglobin (Hb), platelet count, creatinine, and C-reactive protein (CRP) were collected at the time of the first hospital admission, immediately after the confirmation of lung cancer diagnosis and prior to the initiation of any treatment, regardless of treatment type. This approach ensured uniformity in data collection and minimized the influence of treatment-related changes on baseline biological parameters. We have now clarified this point in the revised version of the manuscript. 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? Response to reviewer: Thank you for your valuable comment. The point allocation in Table 3 was not based solely on the statistical significance (p-values), but rather on the β coefficients obtained from multivariate logistic regression, which reflect the strength of association between each variable and the outcome (VTE occurrence). To construct the score, we applied a commonly used method in predictive model development, which involves: Dividing each β coefficient by the smallest absolute β coefficient in the model (used as a reference), Rounding the result to the nearest integer to assign the corresponding weight (score point). In our model, the smallest β coefficient was that of “Presence of metastases”, with a value of 1.197. We then applied the following calculations: Hemoglobin < 10 g/dL: 1.508 / 1.197 = 1.26, rounded to 1 point Presence of metastases: 1.197 / 1.197 = 1, rounded to 1 point Histological type difficult to classify (NSCLC): 1.875 / 1.197 = 1.57, rounded to 2 points Active smoking: 1.431 / 1.197 = 1.19, rounded to 1 point Therefore, even though active smoking had a low p-value, its β coefficient was not the highest among the predictors. The histological type variable had the largest coefficient and thus received the highest weight (2 points). This approach ensures that the scoring reflects the relative contribution of each predictor rather than just their individual statistical significance. 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Response to reviewer: Thank you for raising this important point. It is not uncommon for a variable to be non-significant in univariate analysis but become statistically significant in multivariate analysis. In our case, the hemoglobin level <10 g/dL had a p-value of 0 .228 in univariate analysis, yet became statistically significant (p = 0.039) in multivariate analysis. This phenomenon may be explained by the presence of confounding or interaction effects between variables. In univariate analysis, each variable is assessed in isolation, without adjusting for the influence of other potential covariates. In contrast, multivariate analysis accounts for the combined and adjusted effects of multiple predictors. Once other variables are included in the model — such as metastatic status, histological subtype, and smoking — the independent contribution of hemoglobin to VTE risk becomes more evident. Moreover, the decision to retain variables for multivariate modeling was based not only on statistical thresholds but also on epidemiological and clinical relevance. In line with the approach proposed by Bursac et al. (2008), we included variables with univariate p-values below 0.250, as this cutoff has been shown to reduce the risk of omitting important variables too early. This strategy was also recommended by the epidemiologists of our institution during the study design phase. References: ( Source: Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008 Dec 16;3:17. doi: 10.1186/1751-0473-3-17. PMID: 19087314; PMCID: PMC2633005. ) The reference was included as the ninth entry in the reference list; however, the remaining references were not updated accordingly. Therefore, although the univariate association between low hemoglobin and VTE was not statistically significant, we retained it in the multivariate model due to its known pathophysiological plausibility in cancer-associated thrombosis, and its potential contribution to a more robust predictive model. After adjustment for other covariates, the association became statistically significant. We have added a clarification to this effect in the revised Methods section. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 05 Sep 2025 CHIRINE MOUSSA , Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Tunisia 05 Sep 2025 Author Response 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients ... Continue reading 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? Response to reviewer Thank you for this relevant comment. We acknowledge that lung cancer management has significantly evolved over the past decade, particularly with the introduction of immune checkpoint inhibitors and targeted therapies. However, it is important to note that in Tunisia, a low-to-middle-income country, access to these innovative therapies remains extremely limited. Immunotherapy and targeted treatments have only been introduced into clinical practice in the past two years, and only a restricted number of molecules are currently available, due to their high cost and limited accessibility within the public health system. Consequently, throughout the study period, which spans nearly ten years, the vast majority of patients included were treated with conventional chemotherapy protocols. This contributes to the overall consistency of treatment regimens across the cohort. Moreover, at the time of inclusion, no patients in the VTE group had received immune checkpoint inhibitors or anti-angiogenic agents before the thromboembolic event. Thus, the potential impact of these newer therapies on the incidence of VTE was not a confounding factor in our analysis. We have now clarified this point in the revised manuscript. 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? Response to reviewer: Thank you for your insightful question. In our manuscript, we made a specific distinction between chemotherapy in general and platinum-based chemotherapy because of the well-established association between platinum compounds and increased risk of venous thromboembolism (VTE), particularly in lung cancer. This is why platinum-based chemotherapy is explicitly included in risk assessment tools such as the PROTECHT score. To clarify: “Chemotherapy” is a broad term that refers to any cytotoxic anticancer treatment, regardless of the drug class. “Platinum-based chemotherapy” refers specifically to regimens that include platinum compounds, such as cisplatin or carboplatin. Therefore, while platinum-based chemotherapy is indeed a subset of chemotherapy, we chose to identify it separately in our analysis due to its particular thrombotic profile and relevance to the pathophysiology of VTE in lung cancer patients. 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? Response to reviewer: Thank you for your question. For all enrolled patients, including those without VTE, the data on BMI, white blood cell count (WBC), hemoglobin (Hb), platelet count, creatinine, and C-reactive protein (CRP) were collected at the time of the first hospital admission, immediately after the confirmation of lung cancer diagnosis and prior to the initiation of any treatment, regardless of treatment type. This approach ensured uniformity in data collection and minimized the influence of treatment-related changes on baseline biological parameters. We have now clarified this point in the revised version of the manuscript. 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? Response to reviewer: Thank you for your valuable comment. The point allocation in Table 3 was not based solely on the statistical significance (p-values), but rather on the β coefficients obtained from multivariate logistic regression, which reflect the strength of association between each variable and the outcome (VTE occurrence). To construct the score, we applied a commonly used method in predictive model development, which involves: Dividing each β coefficient by the smallest absolute β coefficient in the model (used as a reference), Rounding the result to the nearest integer to assign the corresponding weight (score point). In our model, the smallest β coefficient was that of “Presence of metastases”, with a value of 1.197. We then applied the following calculations: Hemoglobin < 10 g/dL: 1.508 / 1.197 = 1.26, rounded to 1 point Presence of metastases: 1.197 / 1.197 = 1, rounded to 1 point Histological type difficult to classify (NSCLC): 1.875 / 1.197 = 1.57, rounded to 2 points Active smoking: 1.431 / 1.197 = 1.19, rounded to 1 point Therefore, even though active smoking had a low p-value, its β coefficient was not the highest among the predictors. The histological type variable had the largest coefficient and thus received the highest weight (2 points). This approach ensures that the scoring reflects the relative contribution of each predictor rather than just their individual statistical significance. 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Response to reviewer: Thank you for raising this important point. It is not uncommon for a variable to be non-significant in univariate analysis but become statistically significant in multivariate analysis. In our case, the hemoglobin level <10 g/dL had a p-value of 0 .228 in univariate analysis, yet became statistically significant (p = 0.039) in multivariate analysis. This phenomenon may be explained by the presence of confounding or interaction effects between variables. In univariate analysis, each variable is assessed in isolation, without adjusting for the influence of other potential covariates. In contrast, multivariate analysis accounts for the combined and adjusted effects of multiple predictors. Once other variables are included in the model — such as metastatic status, histological subtype, and smoking — the independent contribution of hemoglobin to VTE risk becomes more evident. Moreover, the decision to retain variables for multivariate modeling was based not only on statistical thresholds but also on epidemiological and clinical relevance. In line with the approach proposed by Bursac et al. (2008), we included variables with univariate p-values below 0.250, as this cutoff has been shown to reduce the risk of omitting important variables too early. This strategy was also recommended by the epidemiologists of our institution during the study design phase. References: ( Source: Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008 Dec 16;3:17. doi: 10.1186/1751-0473-3-17. PMID: 19087314; PMCID: PMC2633005. ) The reference was included as the ninth entry in the reference list; however, the remaining references were not updated accordingly. Therefore, although the univariate association between low hemoglobin and VTE was not statistically significant, we retained it in the multivariate model due to its known pathophysiological plausibility in cancer-associated thrombosis, and its potential contribution to a more robust predictive model. After adjustment for other covariates, the association became statistically significant. We have added a clarification to this effect in the revised Methods section. 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? Response to reviewer Thank you for this relevant comment. We acknowledge that lung cancer management has significantly evolved over the past decade, particularly with the introduction of immune checkpoint inhibitors and targeted therapies. However, it is important to note that in Tunisia, a low-to-middle-income country, access to these innovative therapies remains extremely limited. Immunotherapy and targeted treatments have only been introduced into clinical practice in the past two years, and only a restricted number of molecules are currently available, due to their high cost and limited accessibility within the public health system. Consequently, throughout the study period, which spans nearly ten years, the vast majority of patients included were treated with conventional chemotherapy protocols. This contributes to the overall consistency of treatment regimens across the cohort. Moreover, at the time of inclusion, no patients in the VTE group had received immune checkpoint inhibitors or anti-angiogenic agents before the thromboembolic event. Thus, the potential impact of these newer therapies on the incidence of VTE was not a confounding factor in our analysis. We have now clarified this point in the revised manuscript. 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? Response to reviewer: Thank you for your insightful question. In our manuscript, we made a specific distinction between chemotherapy in general and platinum-based chemotherapy because of the well-established association between platinum compounds and increased risk of venous thromboembolism (VTE), particularly in lung cancer. This is why platinum-based chemotherapy is explicitly included in risk assessment tools such as the PROTECHT score. To clarify: “Chemotherapy” is a broad term that refers to any cytotoxic anticancer treatment, regardless of the drug class. “Platinum-based chemotherapy” refers specifically to regimens that include platinum compounds, such as cisplatin or carboplatin. Therefore, while platinum-based chemotherapy is indeed a subset of chemotherapy, we chose to identify it separately in our analysis due to its particular thrombotic profile and relevance to the pathophysiology of VTE in lung cancer patients. 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? Response to reviewer: Thank you for your question. For all enrolled patients, including those without VTE, the data on BMI, white blood cell count (WBC), hemoglobin (Hb), platelet count, creatinine, and C-reactive protein (CRP) were collected at the time of the first hospital admission, immediately after the confirmation of lung cancer diagnosis and prior to the initiation of any treatment, regardless of treatment type. This approach ensured uniformity in data collection and minimized the influence of treatment-related changes on baseline biological parameters. We have now clarified this point in the revised version of the manuscript. 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? Response to reviewer: Thank you for your valuable comment. The point allocation in Table 3 was not based solely on the statistical significance (p-values), but rather on the β coefficients obtained from multivariate logistic regression, which reflect the strength of association between each variable and the outcome (VTE occurrence). To construct the score, we applied a commonly used method in predictive model development, which involves: Dividing each β coefficient by the smallest absolute β coefficient in the model (used as a reference), Rounding the result to the nearest integer to assign the corresponding weight (score point). In our model, the smallest β coefficient was that of “Presence of metastases”, with a value of 1.197. We then applied the following calculations: Hemoglobin < 10 g/dL: 1.508 / 1.197 = 1.26, rounded to 1 point Presence of metastases: 1.197 / 1.197 = 1, rounded to 1 point Histological type difficult to classify (NSCLC): 1.875 / 1.197 = 1.57, rounded to 2 points Active smoking: 1.431 / 1.197 = 1.19, rounded to 1 point Therefore, even though active smoking had a low p-value, its β coefficient was not the highest among the predictors. The histological type variable had the largest coefficient and thus received the highest weight (2 points). This approach ensures that the scoring reflects the relative contribution of each predictor rather than just their individual statistical significance. 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Response to reviewer: Thank you for raising this important point. It is not uncommon for a variable to be non-significant in univariate analysis but become statistically significant in multivariate analysis. In our case, the hemoglobin level <10 g/dL had a p-value of 0 .228 in univariate analysis, yet became statistically significant (p = 0.039) in multivariate analysis. This phenomenon may be explained by the presence of confounding or interaction effects between variables. In univariate analysis, each variable is assessed in isolation, without adjusting for the influence of other potential covariates. In contrast, multivariate analysis accounts for the combined and adjusted effects of multiple predictors. Once other variables are included in the model — such as metastatic status, histological subtype, and smoking — the independent contribution of hemoglobin to VTE risk becomes more evident. Moreover, the decision to retain variables for multivariate modeling was based not only on statistical thresholds but also on epidemiological and clinical relevance. In line with the approach proposed by Bursac et al. (2008), we included variables with univariate p-values below 0.250, as this cutoff has been shown to reduce the risk of omitting important variables too early. This strategy was also recommended by the epidemiologists of our institution during the study design phase. References: ( Source: Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008 Dec 16;3:17. doi: 10.1186/1751-0473-3-17. PMID: 19087314; PMCID: PMC2633005. ) The reference was included as the ninth entry in the reference list; however, the remaining references were not updated accordingly. Therefore, although the univariate association between low hemoglobin and VTE was not statistically significant, we retained it in the multivariate model due to its known pathophysiological plausibility in cancer-associated thrombosis, and its potential contribution to a more robust predictive model. After adjustment for other covariates, the association became statistically significant. We have added a clarification to this effect in the revised Methods section. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 20 Oct 2023 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 2 (revision) 18 Aug 25 read read Version 1 20 Oct 23 read read Ping Wang , The Fourth Hospital of Hebei Medical University, Shijiazhuang, China Georgia Gomatou , National and Kapodistrian University of Athens, Athens, Greece; National and Kapodistrian University of Athens School of Medicine, Athens, Greece Marc Vasse , Université Paris-Saclay, Foch Hospital, Suresnes, France Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Vasse M. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Feb 2026 | for Version 2 Marc Vasse , Université Paris-Saclay, Foch Hospital, Suresnes, France 0 Views copyright © 2026 Vasse M. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions In this paper, the authors describe a new score to identify the thrombotic risk in lung cancer patients treated by "classical chemotherapy" used in low-to-middle-income countries. 1) The introduction is too long and bibliography is not relevant. The frequency of thrombosis in lung cancer patients is not so high (20 to 30 %) as indicated, and the reference 1 applies to patients treated by check point inhibitors, that is not the case of the patients of this study. 2) I am surprised that patients are divided (fig 1) as only PE. No patients had both deep venous thrombosis and pulmonary embolism? 3) All cases of VTE are indicated as 102. Surprisingly, the sum of "only PE" + "only DVT " + only SVT is 108. 4) The authors indicate in the discussion that their score as a poor predictive value. Usually, despite a poor discriminating capacity in lung cancer patients, the Khorana score (KS) is used. A comparison of the Khorana score with this new score could be interesting. In addition, in lung cancer, KS is predictive of mortality (PMID 29806470). Is your score predictive of the mortality? Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests I am currently working to identify new thrombotic risk factors in patients with lung cancer Reviewer Expertise Coagulation, cancer associated thrombosis I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Vasse M. Peer Review Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.186248.r455484) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1388/v2#referee-response-455484 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Gomatou G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 23 Aug 2025 | for Version 2 Georgia Gomatou , Oncology Unit, Third Department of Medicine, “Sotiria” General Hospital for Diseases of the Chest, National and Kapodistrian University of Athens, Athens, Greece; National and Kapodistrian University of Athens School of Medicine, Athens, Attica, Greece 0 Views copyright © 2025 Gomatou G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The authors have successfully incorporated the reviewers' suggestions. No further comments. Competing Interests No competing interests were disclosed. Reviewer Expertise Medical Oncology, Thoracic Oncology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Gomatou G. Peer Review Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.186248.r406432) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1388/v2#referee-response-406432 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Gomatou G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 06 Nov 2024 | for Version 1 Georgia Gomatou , Oncology Unit, Third Department of Medicine, “Sotiria” General Hospital for Diseases of the Chest, National and Kapodistrian University of Athens, Athens, Greece; National and Kapodistrian University of Athens School of Medicine, Athens, Attica, Greece 0 Views copyright © 2024 Gomatou G. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This is an original study describing a prediction score of VTE in patients with lung cancer. In general, the manuscript is well-written and the methods and results are clearly presented. My suggestions in order to improve the paper: 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Medical Oncology, Thoracic Oncology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 05 Sep 2025 CHIRINE MOUSSA, Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Tunisia 1. Why are the non-inclusion criteria described seperately from exclusion criteria? Please combine. Response to the reviewer: Thank you for your valuable comment regarding the separation of non-inclusion and exclusion criteria. In our protocol, we initially presented them separately to reflect the different stages of patient selection: non-inclusion criteria correspond to conditions preventing initial eligibility (e.g., lack of histological confirmation), while exclusion criteria relate to factors identified after preliminary assessment (e.g., comorbidities, acute events, or unusable records). However, to improve clarity and according to your suggestion, we are happy to combine both into a single section titled “Non-inclusion and exclusion criteria” for simplicity and better readability. Proposed combined criteria: Histologically unconfirmed bronchopulmonary carcinoma (BPC) Secondary pulmonary localizations History of: • Other neoplasms • Acute phase of myocardial infarction (MI) • Acute phase of stroke Unusable medical records 2. The limitations should be included in the Discussion section (last paragraph of Discussion) and not in the Conclusions. Response to reviewer: Thank you for your valuable suggestion. We agree that discussing the study’s limitations is more appropriate in the Discussion section. We confirm that these limitations are already addressed within a dedicated paragraph of the Discussion. Accordingly, we will remove the sentence referring to the limitations from the Conclusions section to avoid redundancy and improve the overall clarity of the manuscript. 3. In Figure 1 you use the term 'randomization'. However, the process of randomly allocating patients in each group is not randomization. Please delete the term. Response to the reviewer: Thank you for your valuable comment regarding the use of the term “randomization” in Figure 1. We acknowledge that the allocation process used in our study was based on generating “random” numbers from the sequence of patients’ medical record numbers. This method does not constitute a strict randomization procedure as per clinical trial standards, since medical record numbers are assigned sequentially and may introduce allocation bias. Therefore, to avoid any misunderstanding, we have removed the term “randomization” from Figure 1 and replaced it with “allocation” or a similar neutral term that better reflects the actual process. We appreciate your careful review and hope this clarifies the method used. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Gomatou G. Peer Review Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.152109.r335912) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-1388/v1#referee-response-335912 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Wang P. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 15 May 2024 | for Version 1 Ping Wang , The Fourth Hospital of Hebei Medical University, Shijiazhuang, China 0 Views copyright © 2024 Wang P. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Many literatures have reported that the incidence rate of tumor with VTE is significantly higher than that of other diseases, and the incidence rate of lung cancer with VTE is higher. There are many studies on the risk factors of lung cancer combined with VTE, and many suggest that pathological types, stages, and other factors are related to the occurrence of VTE. This manuscript introduces several processes for establishing a VTE screening model, but some issues still need to be discussed. 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? I cannot comment. A qualified statistician is required. Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise Lung cancer and VTE, lung cancer and infection. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 05 Sep 2025 CHIRINE MOUSSA, Pneumology 1, Abderrahmen Mami Pneumology and Phthisiology Hospital, Ariana, Tunisia 1. The enrolled patients have a large annual span of nearly ten years. The treatment of lung cancer has also undergone significant changes over the past decade. When were patients enrolled in each group? How to maintain consistency in the inclusion criteria for patients over the past decade, especially whether current immune checkpoint inhibitors and anti angiogenic drugs have an impact on VTE? Response to reviewer Thank you for this relevant comment. We acknowledge that lung cancer management has significantly evolved over the past decade, particularly with the introduction of immune checkpoint inhibitors and targeted therapies. However, it is important to note that in Tunisia, a low-to-middle-income country, access to these innovative therapies remains extremely limited. Immunotherapy and targeted treatments have only been introduced into clinical practice in the past two years, and only a restricted number of molecules are currently available, due to their high cost and limited accessibility within the public health system. Consequently, throughout the study period, which spans nearly ten years, the vast majority of patients included were treated with conventional chemotherapy protocols. This contributes to the overall consistency of treatment regimens across the cohort. Moreover, at the time of inclusion, no patients in the VTE group had received immune checkpoint inhibitors or anti-angiogenic agents before the thromboembolic event. Thus, the potential impact of these newer therapies on the incidence of VTE was not a confounding factor in our analysis. We have now clarified this point in the revised manuscript. 2. What is the difference between chemotherapy and platinum based chemotherapy? Does chemotherapy include chemotherapy with platinum containing drugs? Response to reviewer: Thank you for your insightful question. In our manuscript, we made a specific distinction between chemotherapy in general and platinum-based chemotherapy because of the well-established association between platinum compounds and increased risk of venous thromboembolism (VTE), particularly in lung cancer. This is why platinum-based chemotherapy is explicitly included in risk assessment tools such as the PROTECHT score. To clarify: “Chemotherapy” is a broad term that refers to any cytotoxic anticancer treatment, regardless of the drug class. “Platinum-based chemotherapy” refers specifically to regimens that include platinum compounds, such as cisplatin or carboplatin. Therefore, while platinum-based chemotherapy is indeed a subset of chemotherapy, we chose to identify it separately in our analysis due to its particular thrombotic profile and relevance to the pathophysiology of VTE in lung cancer patients. 3. You collect relevant data and blood tests for enrolled patients. At what time point were the BMI, WBC, Hb, Platelets, Creatinine, and CRP data collected from patients? Especially for non VTE patients, which time point data is appropriate? Response to reviewer: Thank you for your question. For all enrolled patients, including those without VTE, the data on BMI, white blood cell count (WBC), hemoglobin (Hb), platelet count, creatinine, and C-reactive protein (CRP) were collected at the time of the first hospital admission, immediately after the confirmation of lung cancer diagnosis and prior to the initiation of any treatment, regardless of treatment type. This approach ensured uniformity in data collection and minimized the influence of treatment-related changes on baseline biological parameters. We have now clarified this point in the revised version of the manuscript. 4. Is there any basis researches for the predicted score in Table 3? The P-value for active smoking is the lowest, why is it only 1 point, while the Historical type poor or unidentified NSCLC is 2 points? Response to reviewer: Thank you for your valuable comment. The point allocation in Table 3 was not based solely on the statistical significance (p-values), but rather on the β coefficients obtained from multivariate logistic regression, which reflect the strength of association between each variable and the outcome (VTE occurrence). To construct the score, we applied a commonly used method in predictive model development, which involves: Dividing each β coefficient by the smallest absolute β coefficient in the model (used as a reference), Rounding the result to the nearest integer to assign the corresponding weight (score point). In our model, the smallest β coefficient was that of “Presence of metastases”, with a value of 1.197. We then applied the following calculations: Hemoglobin < 10 g/dL: 1.508 / 1.197 = 1.26, rounded to 1 point Presence of metastases: 1.197 / 1.197 = 1, rounded to 1 point Histological type difficult to classify (NSCLC): 1.875 / 1.197 = 1.57, rounded to 2 points Active smoking: 1.431 / 1.197 = 1.19, rounded to 1 point Therefore, even though active smoking had a low p-value, its β coefficient was not the highest among the predictors. The histological type variable had the largest coefficient and thus received the highest weight (2 points). This approach ensures that the scoring reflects the relative contribution of each predictor rather than just their individual statistical significance. 5. In univariate analysis the result of hemoglobin level<10 g/l was P=0.228, while in multivariate analysis was P=0.039? What are the criteria for incorporating multiple factor analysis and comparison? Response to reviewer: Thank you for raising this important point. It is not uncommon for a variable to be non-significant in univariate analysis but become statistically significant in multivariate analysis. In our case, the hemoglobin level <10 g/dL had a p-value of 0 .228 in univariate analysis, yet became statistically significant (p = 0.039) in multivariate analysis. This phenomenon may be explained by the presence of confounding or interaction effects between variables. In univariate analysis, each variable is assessed in isolation, without adjusting for the influence of other potential covariates. In contrast, multivariate analysis accounts for the combined and adjusted effects of multiple predictors. Once other variables are included in the model — such as metastatic status, histological subtype, and smoking — the independent contribution of hemoglobin to VTE risk becomes more evident. Moreover, the decision to retain variables for multivariate modeling was based not only on statistical thresholds but also on epidemiological and clinical relevance. In line with the approach proposed by Bursac et al. (2008), we included variables with univariate p-values below 0.250, as this cutoff has been shown to reduce the risk of omitting important variables too early. This strategy was also recommended by the epidemiologists of our institution during the study design phase. References: ( Source: Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008 Dec 16;3:17. doi: 10.1186/1751-0473-3-17. PMID: 19087314; PMCID: PMC2633005. ) The reference was included as the ninth entry in the reference list; however, the remaining references were not updated accordingly. Therefore, although the univariate association between low hemoglobin and VTE was not statistically significant, we retained it in the multivariate model due to its known pathophysiological plausibility in cancer-associated thrombosis, and its potential contribution to a more robust predictive model. After adjustment for other covariates, the association became statistically significant. We have added a clarification to this effect in the revised Methods section. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Wang P. Peer Review Report For: A novel risk score for venous thromboembolism in lung cancer patients: a retrospective cohort study [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 12 :1388 ( https://doi.org/10.5256/f1000research.152109.r253369) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. 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