A Prediction Model for Chemotherapy-Induced Thrombocytopenia Based on Real-World Data and a Close Relationship Between AST/ALT Ratio and Platelet Count in Patients with Solid Tumors

OBJECTIVE

Chemotherapy-induced thrombocytopenia (CIT) can lead to chemotherapy dose delay or reduction, and even serious bleeding. This study aimed to develop a CIT-predicting model based on the laboratory indices of cancer patients undergoing chemotherapy.

MATERIAL AND METHODS

From Jun 1, 2017 to Dec 30, 2021, a total of 2043 patients who had received 7676 cycles of chemotherapy were retrospectively enrolled. A logistic regression analysis was performed to identify predictive factors, on the basis of which a nomogram model for predicting CIT was established. A bootstrapping technique was applied for internal validation. A generalized additive mixed model (GAMM) was constructed to analyze the trends in the changes of aspartate aminotransferase (AST), ratio of AST to alanine transaminase (ALT) (AST/ALT ratio), and platelet (PLT) count in patients with solid tumors. P values ≤0.05 were considered statistically significant.

RESULTS

The patient-based incidence of CIT was 20.51% and the cycle-based incidence was 10.01%. The multivariate analysis showed that AST level, AST/ALT ratio, and total bilirubin (Tbil), white blood cell (WBC), platelet (PLT), hemoglobin (Hb) levels were significantly associated with the risk of CIT. The GAMM analysis showed that PLT level was inversely associated with AST/ALT ratio and AST level, more significantly with AST/ALT ratio. And both exhibited statistically predictive abilities for CIT. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.793, a sensitivity of 0.543 and a specificity of 0.930.

CONCLUSION

The AST/ALT ratio was inversely associated with the CIT risk in cancer patients. The GAMM model based on laboratory indices presented a high accuracy in predicting the risk of CIT, and a potential to be translated into clinical management.

Predicting chemotherapy-induced thrombocytopenia in cancer patients with solid tumors or lymphoma

Purpose

Chemotherapy-induced thrombocytopenia is a serious complication in chemotherapy-treated patients. Identification of patients at risk for chemotherapy-induced thrombocytopenia could have clinical value in personalized management of patients and optimized administration of prophylactic thrombopoietic agents. The aim of this study was to develop a predictive model for chemotherapy-induced thrombocytopenia (platelet count < 100,000/µl) in cancer patients undergoing chemotherapy.

Methods

A total of 14 covariates were prospectively assessed as explanatory variables in a cohort of consecutive patients with solid tumors or lymphoma. A multivariable logistic regression model was developed after univariable analysis. A bootstrapping technique was applied for internal validation.

Results

Data from 305 patients during 1732 chemotherapy cycles were considered for analysis. Forty-eight patients (15.73%) developed chemotherapy-induced thrombocytopenia during their treatment course. The multivariable model exhibited three final predictors for chemotherapy-induced thrombocytopenia, including high ferritin (odds ratio, 4.41; bootstrap P = 0.001), estimated glomerular filtration rate <60 ml/min/1.73 m2(odds ratio, 3.08; bootstrap P = 0.005), and body mass index <23 kg/m2(odds ratio, 2.23; bootstrap P = 0.044). The main characteristics of the model include sensitivity 75%, specificity 65.4%, positive likelihood ratio 2.16, and negative likelihood ratio 0.382. Moreover, the model was well calibrated (Hosmer–Lemeshow P = 0.713) and the area under the receiver operating characteristic curve was 0.735 (95% confidence interval, 0.654–0.816; P < 0.001).

Conclusions

We developed a predictive model for chemotherapy-induced thrombocytopenia based on readily available and easily assessable clinical and laboratory factors. This study may provide a valuable insight to guide optimized treatment of cancer patients. Further studies with larger sample size are warranted.