Predictors of Venous Thromboembolism in Patients With Testicular Germ Cell Tumors: A Retrospective Study

Simple, Effective and Validated. VTE CASE Risk Assessment Score for Venous Thromboembolism in Metastatic Germ Cell Tumour Patients Before First-Line Chemotherapy

BACKGROUND

Venous thromboembolism (VTE) may jeopardise excellent treatment results of germ cell tumours (GCT). We previously constructed a VTE risk score for GCT patients qualified for first-line chemotherapy (CTH), including vein compression, clinical stage (CS) and haemoglobin concentration.

AIM

Validating our score in a separate cohort and establishing the cut-off point for the score. Re-assessing the numerical score in the training cohort.

MATERIALS AND METHODS

We retrospectively analysed a new cohort of GCT patients staged IS-IIIC. Area under the curve of receiver-operating characteristic (AUC-ROC) was calculated for the developed score, Khorana Risk Score (KRS) and Padua Prediction Score (PPS). AUC-ROC of the integer score was calculated for the training cohort. Cut-off point was established by Youden's and Liu's indices.

RESULTS

Among 336 eligible patients in the validation cohort, VTE occurred in 41 (12.2%). AUC-ROC for our score, KRS and PPS were 0.818 (95% confidence interval (CI): 0.746-0.891), 0.608 (0.529-0.688) and 0.634 (0.547-0.720), respectively, p < 0.001. The optimal cut-off point for a low/high risk was 6 (≤ 6 vs. ≥ 7). In the training cohort, 369 patients had complete data on vein compression. AUC-ROC for our score, KRS and PPS were 0.819 (95% CI: 0.758-0.879), 0.710 (0.637-0.782) and 0.725 (0.651-0.800), p ≤ 0.001 and 0.015, respectively. Positive and negative predictive values were 30.8% and 96.5%, respectively.

CONCLUSIONS

Our VTE risk score is a handy tool for GCT patients before first-line CTH for metastatic disease. Outperforming KRS and PPS, it has a good discriminatory value, especially for identifying low-risk patients.

Development and validation of a nomogram model for predicting venous thromboembolism risk in lung cancer patients treated with immune checkpoint inhibitors: A cohort study in China

OBJECTIVE

Venous thromboembolism (VTE) poses a significant threat to lung cancer patients, particularly those receiving treatment with immune checkpoint inhibitors (ICIs). We aimed to develop and validate a nomogram model for predicting the occurrence of VTE in lung cancer patients undergoing ICI therapy.

METHODS

The data for this retrospective cohort study was collected from cancer patients admitted to Chongqing University Cancer Hospital for ICI treatment between 2019 and 2022. The research data is divided into training and validation sets using a 7:3 ratio. Univariate and multivariate analyses were employed to identify risk factors for VTE. Based on these analyses, along with clinical expertise, a nomogram model was crafted. The model's predictive accuracy was assessed through receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis, clinical impact curve, and other relevant metrics.

RESULTS

The initial univariate analysis pinpointed 13 potential risk factors for VTE. The subsequent stepwise multivariate regression analysis identified age, Karnofsky performance status, chemotherapy, targeted, platelet count, lactate dehydrogenase, monoamine oxidase, D-dimer, fibrinogen, and white blood cell count as significant predictors of VTE. These 10 variables were the foundation for a predictive model, illustrated by a clear and intuitive nomogram. The model's discriminative ability was demonstrated by the ROC curve, which showed an area under the curve of 0.815 (95% CI 0.772-0.858) for the training set, and 0.753 (95% CI 0.672-0.835) for the validation set. The model's accuracy was further supported by Brier scores of 0.068 and 0.080 for the training and validation sets, respectively, indicating a strong correlation with actual outcomes.

CONCLUSION

We have successfully established and validated a nomogram model for predicting VTE risk in lung cancer patients treated with ICIs.

The association between lactate dehydrogenase to serum albumin ratio and in-hospital mortality in patients with pulmonary embolism: a retrospective analysis of the MIMIC-IV database

Background

Lactate dehydrogenase (LDH) and albumin (ALB) were found to be significantly correlated with mortality in pulmonary embolism (PE) patients. However, data regarding the LDH/ALB ratio (LAR) in patients with acute PE are scanty. Therefore, the aim of this study was to investigate the association between LAR and the risk of mortality in patients with acute PE.

Methods

A retrospective cohort study was conducted on patients with acute PE represented in the Medical Information Mart for Intensive Care IV (MIMIC-IV). A receiver operating characteristic (ROC) curve analysis and calibration curve were used to assess the accuracy of the LAR for predicting mortality in patients with acute PE. We utilized Cox regression analysis to determine adjusted hazard ratios (HR) and 95% confidence interval (CI). Survival curves were used to evaluate a connection between the LAR and prognosis in patients with acute PE.

Results

The study comprised 581 patients, and the 30-day all-cause mortality rate was 7.7%. We observed a higher LAR in the non-survival group compared to the surviving group (21.24 ± 21.22 vs. 8.99 ± 7.86, p < 0.0001). The Kaplan-Meier analysis showed that patients with an elevated LAR had a significantly lower likelihood of surviving the 30-day mortality compared to those with a low LAR. Cox regression analysis showed that LAR (HR = 1.04, 95% CI: 1.03-1.05) might have associations with 30-day mortality in patients with acute PE. This result was supported by sensitivity analyses. According to the results of the ROC curve analysis, the LAR's prediction of 30-day mortality in patients with acute PE yielded an area under the ROC curve of 0.73. A calibration curve showed LAR is well calibrated.

Conclusion

Our research suggests LAR monitoring may be promising as a prognostic marker among patients with acute PE.

Thrombosis Rates and Genetic Thrombophilia Risk Among Patients With Advanced Germ Cell Tumors Treated With Chemotherapy

INTRODUCTION

Men with advanced germ cell tumors (GCT) treated with chemotherapy are at high risk of venous thromboembolism (VTE). Predictors of VTE may identify patients who would benefit from prophylactic anticoagulation.

PATIENTS AND METHODS

Men with advanced GCT (Stage IS, II, III) treated with chemotherapy were identified at 2 centers. High genomic risk was defined from a 5 single nucleotide polymorphism (SNP) germline panel. Logistic regression was used to evaluate the impact of genomic risk on VTE within 6 months of chemotherapy initiation. Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) was used to build models to predict VTE based on clinical variables and an 86 SNP panel.

RESULTS

This 123-patient cohort experienced a VTE rate of 26% with an incidence of high genomic risk of 21%. Men with high genomic risk did not have a significantly higher VTE rate (31%, 8/26) than men with low genomic risk (25%, 24/97), unadjusted OR 1.4 (95% CI 0.5-3.5, P = .54). Incorporation of clinical variables (Khorana score, N3 status and elevated LDH) resulted in adjusted OR 2.1 (95% CI 0.7-6.5, P = .18). A combined model using clinical variables and 86 SNPs performed similarly (AUC 0.77) compared to clinical variables alone (AUC 0.72).

CONCLUSIONS

A previously established 5-SNP panel was not associated with VTE among patients with GCT receiving chemotherapy. However, multivariable models based on clinical variables alone warrant further validation to inform prophylactic anticoagulation strategies.

A nomogram for predicting the risk of venous thromboembolism in patients with solid cancers

Cancer patients with venous thromboembolism (VTE) are prone to poor prognoses. Thus, we aimed to develop a nomogram to predict the risk of VTE in these patients. We retrospectively analyzed 791 patients diagnosed with solid tumors between January 2017 and May 2021 at Tongji Hospital. Univariate logistic analysis and multivariate logistic regression were adopted in this study. Our results indicated that age ≥ 60 years, tumor stages III-IV, platelet distribution width (PDW) ≤ 12.6%, albumin concentration ≤ 38.8 g/L, lactate dehydrogenase (LDH) concentration ≥ 198 U/L, D-dimer concentration ≥ 1.72 µg/mL, blood hemoglobin concentration ≤ 100 g/dL or the use of erythropoiesis-stimulating agents and cancer types were independent risk factors. The nomogram prediction model was developed based on the regression coefficients of these variables. We assessed the performance of the nomogram by calibration plot and the area under the receiver operating characteristic curve and compared it with the Khorana score. The concordance index (C- index) of the nomogram was 0.852 [95% confidence interval (CI) 0.823 to 0.880], while the Khorana score was 0.681 (95% CI 0.639 to 0.723). Given its performance, this nomogram could be used to select cancer patients at high risk for VTE and guide thromboprophylaxis treatment in clinical practice, provided it is validated in an external cohort.

Cancer-Associated Thrombosis: A Clinical Scoping Review of the Risk Assessment Models Across Solid Tumours and Haematological Malignancies

Cancer-associated thrombosis (CAT) is a leading cause of death in cancer patients receiving outpatient chemotherapy. The latest guidelines emphasize stratifying the patients in terms of CAT risks periodically. Multiple risk assessment models (RAMs) were developed to classify patients and guide thromboprophylaxis to high-risk patients. This study aimed to discuss and highlight different RAMs across various malignancy types with their related advantages and disadvantages. A scoping review was conducted using predefined search terms in three scientific databases, including Google Scholar, Science Direct, and PubMed. The search for studies was restricted to original research articles that reported risk assessment models published in the last thirteen years (between 2008 and 2021) to cover the most recently published evidence following the development of the principal risk assessment score in 2008. Data charting of the relevant trials, scores, advantages, and disadvantages were done iteratively considering the malignancy type. Of the initially identified 1115 studies, 39 studies with over 67,680 patients were included in the review. In solid organ malignancy, nine risk assessment scores were generated. The first and most known Khorana risk score still offers the best available risk assessment model when used for high-risk populations with a threshold of 2 and above. However, KRS has a limitation of failure to stratify low-risk patients. The COMPASS-CAT score showed the best performance in the lung carcinoma patients who have a higher prevalence of thrombosis than other malignancy subtypes. In testicular germ cell tumours, Bezan et al RAM is a validated good discriminatory RAM for this malignancy subtype. CAT in haematological malignancy seems to be under-investigated and has multiple disease-related, and treatment-related confounding factors. AL-Ani et al score performed efficiently in acute leukemia. In multiple myeloma, both SAVED and IMPEDED VTE scores showed good performance. Despite the availability of different disease-specific scores in lymphoma-related thrombosis, the standard of care needs to be redefined.