Risk factors for delayed chemotherapy-induced nausea and vomiting with low-emetic-risk chemotherapy: a prospective, observational, multicenter study

A deep learning-based interpretable decision tool for predicting high risk of chemotherapy-induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy

OBJECTIVE

This study aims to develop a risk prediction model for chemotherapy-induced nausea and vomiting (CINV) in cancer patients receiving highly emetogenic chemotherapy (HEC) and identify the variables that have the most significant impact on prediction.

METHODS

Data from Tianjin Medical University General Hospital were collected and subjected to stepwise data preprocessing. Deep learning algorithms, including deep forest, and typical machine learning algorithms such as support vector machine (SVM), categorical boosting (CatBoost), random forest, decision tree, and neural network were used to develop the prediction model. After training the model and conducting hyperparameter optimization (HPO) through cross-validation in the training set, the performance was evaluated using the test set. Shapley additive explanations (SHAP), partial dependence plot (PDP), and Local Interpretable Model-Agnostic Explanations (LIME) techniques were employed to explain the optimal model. Model performance was assessed using AUC, F1 score, accuracy, specificity, sensitivity, and Brier score.

RESULTS

The deep forest model exhibited good discrimination, outperforming typical machine learning models, with an AUC of 0.850 (95%CI, 0.780-0.919), an F1 score of 0.757, an accuracy of 0.852, a specificity of 0.863, a sensitivity of 0.784, and a Brier score of 0.082. The top five important features in the model were creatinine clearance (Ccr), age, gender, anticipatory nausea and vomiting, and antiemetic regimen. Among these, Ccr had the most significant predictive value. The risk of CINV decreased with increased Ccr and age, while it was higher in the presence of anticipatory nausea and vomiting, female gender, and non-standard antiemetic regimen.

CONCLUSION

The deep forest model demonstrated good discrimination in predicting the risk of CINV in cancer patients prescribed HEC. Kidney function, as represented by Ccr, played a crucial role in the model's prediction. The clinical application of this predictive tool can help assess individual risks and improve patient care by proactively optimizing the use of antiemetics in cancer patients receiving HEC.

Chemotherapy-Induced Nausea and Vomiting in Patients With Breast Cancer: Risk Factor and Predictive Model Using Classification and Regression Tree (CART)

Introduction Chemotherapy-induced nausea and vomiting (CINV) is a common and debilitating adverse effect of breast cancer chemotherapy. The incidence of CINV in the first cycle of chemotherapy is essential, as it sets the tone for anticipatory CINV and the overall patients' treatment experience. We aimed to investigate the risk factors of first cycle CINV in breast cancer patients and to develop a classification and regression tree (CART) model to predict its occurrence. Methods This is a cross-sectional study that nested in a prospective cohort. One hundred and thirty-seven female breast cancer patients receiving highly emetogenic chemotherapy were included. We used the Common Toxicity Criteria for Adverse Events (CTCAE) version 4.0 to assess patient-reported nausea and vomiting in the first chemotherapy cycle. The proportional difference of CINV between sociodemographic and clinicopathologic variables was analyzed using chi-square, and the strength and direction of the relationship with CINV were analyzed using bivariable logistic regression analysis. Multivariable logistic regression and CART analysis included variables with a p-value <0.250. Results The incidence of first-cycle CINV was 43.1%. The chi-square test revealed a significant association between insurance status and CINV (p<0.001) and between the stage at diagnosis and CINV (p<0.001). Underweight to normal body mass index (BMI) patients are significantly associated with an increased risk of first-cycle CINV (OR =2.17, 95% CI 1.03-4.56, p =0.041). In hierarchical order, three variables (stage at diagnosis, BMI, and age) were included in the CART model, which significantly influenced the probability of first cycle CINV. With an accuracy of 61.3%, the CART model had a sensitivity of 28.8%, a specificity of 85.9%, a positive predictive value of 60.7%, a negative predictive value of 61.5%, and an area under curve (AUC) of 0.602.  Conclusion Breast cancer patients with an underweight to normal BMI have a higher risk of developing first-cycle CINV. Our CART model was better at identifying patients who would not develop CINV than those who would. The CART model may provide a simple and effective way to individualize patient care for first-cycle CINV.

Effectiveness of Palonosetron, 1-Day Dexamethasone, and Aprepitant in Patients Undergoing Carboplatin-Based Chemotherapy

INTRODUCTION

Dexamethasone (DEX)-sparing strategy with 5-hydroxytryptamine-3 receptor antagonist (5HT3RA) and aprepitant (APR), as triplet antiemetic prophylaxis, is associated with poor control of delayed chemotherapy-induced nausea and vomiting (CINV) in patients receiving carboplatin (CBDCA)-based chemotherapy. This study aimed to evaluate whether using palonosetron (PALO) as a 5HT3RA provides superior control with CINV than first-generation (1st) 5HT3RA in triplet antiemetic prophylaxis with a DEX-sparing strategy.

METHODS

Pooled patient-level data from a nationwide, multicenter, and prospective observational study were analyzed to compare the incidence of CINV between patients administered PALO and 1st 5HT3RA in combination with 1-day DEX and APR.

RESULTS

No significant differences were observed in the incidence of CINV, pattern of CINV, or severity of nausea by type of 5HT3RA in triplet antiemetic prophylaxis with DEX-sparing strategy. In both groups, the incidence of nausea gradually increased from day 3, peaked on day 4 or 5, and then declined slowly. The visual analog scale scores in the delayed phase remained high throughout the 7-day observation period.

CONCLUSION

Careful patient selection and symptom monitoring are needed when implementing the DEX-sparing strategy in triplet antiemetic prophylaxis for patients undergoing CBDCA-based chemotherapy. Furthermore, additional strategies may be needed to achieve better control of delayed CINV.

Prevention of Chemotherapy-Induced Nausea and Vomiting in the Older Patient: Optimizing Outcomes

Chemotherapy-induced nausea and vomiting (CINV) are still two of the most feared side effects of cancer therapy. Although major progress in the prophylaxis of CINV has been made during the past 40 years, nausea in particular remains a significant problem. Older patients have a lower risk of CINV than younger patients, but are at a higher risk of severe consequences of dehydration and electrolyte disturbances following emesis. Age-related organ deficiencies, comorbidities, polypharmacy, risk of drug–drug interactions, and lack of compliance all need to be addressed in the older patient with cancer at risk of CINV. Guidelines provide evidence-based recommendations for the prophylaxis of CINV, but none of these guidelines offer specific recommendations for older patients with cancer. This means that the recommendations may lead to overtreatment in some older patients. This review describes the development of antiemetic prophylaxis of CINV focusing on older patients, summarizes recommendations from antiemetic guidelines, describes deficiencies in our knowledge of older patients, summarizes necessary precautions, and suggests some future perspectives for antiemetic research in older patients.

Efficacy of one-day versus multiple-day dexamethasone for chemotherapy-induced nausea and vomiting in lung cancer patients receiving carboplatin-based chemotherapy: a propensity score-matched analysis

PURPOSE

Dexamethasone (DEX)-sparing strategies (one-day DEX) with palonosetron as doublet antiemetic prophylaxis have previously been studied. However, DEX-sparing regimens with 5-hydroxytryptamine-3 receptor antagonist (5-HT₃RA) and aprepitant (APR), as triplet antiemetic prophylaxis, have not been evaluated. This study aimed to evaluate the efficacy of a combination of 5-HT₃RA, APR, and DEX on day 1 of carboplatin (CBDCA)-based chemotherapy in patients with lung cancer.

METHODS

Data were pooled from a nationwide, multicenter, prospective observational study using propensity score-matched analysis to compare the incidence of chemotherapy-induced nausea and vomiting (CINV) between one- and multiple-day DEX regimens in combination with 5-HT₃RA plus APR.

RESULTS

Incidence of delayed nausea was significantly higher in the one-day than in the multiple-day DEX group. Incidence of nausea was also significantly higher in the one-day than in the multiple-day DEX group on days 3-5. Kaplan-Meier curves for nausea showed a significant difference between the two groups; however, there was no significant difference in the occurrence of vomiting or the Kaplan-Meier curves of time to vomiting.

CONCLUSION

To the best of our knowledge, this study is the first to evaluate the efficacy of a DEX-sparing regimen by comparing one- and multiple-day DEX combined with 5-HT₃RA and APR concerning CINV incidence in lung cancer patients receiving CBDCA-based chemotherapy. Antiemetic regimens of one-day DEX result in poor control of delayed nausea; therefore, we recommend the application of the DEX-sparing strategy only after careful patient selection while considering the development of nausea.

Nomogram for Predicting Chemotherapy-Induced Nausea and Vomiting for Breast Cancer Patients

Chemotherapy-induced nausea and vomiting (CINV) is a common side effect of cancer treatment. The factors influencing CINV in breast cancer patients remain unclear. In this study, we developed a nomogram for predicting the occurrence of CINV in this group using prospective clinical data. We pooled data from multiple studies which focused on the emetogenic chemotherapy. Then, we collected 334 breast cancer patients at Hunan Cancer Hospital (training set) to analyze the demographic and clinical variables. Using multivariate logistic regression, we identified the five significant factors that were associated with CINV: history of CINV, chemotherapy regimen, chemotherapy cycle, metastasis, and symptoms of distress. Then, we construct a prediction nomogram. The external validation set comprised an additional 66 patients. The reliability of the nomogram was assessed by bootstrap resampling. The C-index was 0.78 (95% confidence interval [CI], 0.73-0.85) for the training set and 0.74 (95% CI, 0.62-0.85) for the validation set. Calibration curves showed good concordance between predicted and actual occurrence of CINV. In conclusions, our nomogram model can reliably predict the occurrence of CINV in breast cancer patients based on five significant variables, which might be useful in clinical decision-making.

Quantified Kinematics to Evaluate Patient Chemotherapy Risks in Clinic

PURPOSE

Performance status (PS) is a key factor in oncologic decision making, but conventional scales used to measure PS vary among observers. Consumer-grade biometric sensors have previously been identified as objective alternatives to the assessment of PS. Here, we investigate how one such biometric sensor can be used during a clinic visit to identify patients who are at risk for complications, particularly unexpected hospitalizations that may delay treatment or result in low physical activity. We aim to provide a novel and objective means of predicting tolerability to chemotherapy.

METHODS

Thirty-eight patients across three centers in the United States who were diagnosed with a solid tumor with plans for treatment with two cycles of highly emetogenic chemotherapy were included in this single-arm, observational prospective study. A noninvasive motion-capture system quantified patient movement from chair to table and during the get-up-and-walk test. Activity levels were recorded using a wearable sensor over a 2-month period. Changes in kinematics from two motion-capture data points pre- and post-treatment were tested for correlation with unexpected hospitalizations and physical activity levels as measured by a wearable activity sensor.

RESULTS

Among 38 patients (mean age, 48.3 years; 53% female), kinematic features from chair to table were the best predictors for unexpected health care encounters (area under the curve, 0.775 ± 0.029) and physical activity (area under the curve, 0.830 ± 0.080). Chair-to-table acceleration of the nonpivoting knee (t = 3.39; P = .002) was most correlated with unexpected health care encounters. Get-up-and-walk kinematics were most correlated with physical activity, particularly the right knee acceleration (t = -2.95; P = .006) and left arm angular velocity (t = -2.4; P = .025).

CONCLUSION

Chair-to-table kinematics are good predictors of unexpected hospitalizations, whereas the get-up-and-walk kinematics are good predictors of low physical activity.

Patient-Related Risk Factors for Chemotherapy-Induced Nausea and Vomiting: A Systematic Review

Background

Studies have reported that patient-related factors significantly impact the risk of Chemotherapy-Induced Nausea and Vomiting (CINV). The objective of this study was to analyze those risk factors of CINV through a systematic literature review.

Methods

We searched MEDLINE to identify articles that addressed patient-related risk factors of CINV through clinical studies.

Results

A total of 49 articles were selected for this study. A total of 28 patient-related risk-factors that significantly impact the risk of CINV were documented. Three factors are demographically related, 17 factors are intrinsic in nature and innate to patient's physiology or influenced by physiology, and eight factors are extrinsic in nature. At least five studies identified seven risk factors with notable summary odds ratio: history of nausea/vomiting (odds ratio: 3.13, 95% CI 2.40–4.07, p < 0.05), female sex (odds ratio: 2.79, 95% CI 2.26–3.44, p < 0.05), expectancy of CINV (odds ratio: 2.61, 95%CI 1.69–4.02, p < 0.05), younger age (odds ratio: 2.59, 95% CI 2.18–3.07, p < 0.05), anxiety (odds ratio: 2.57, 95% CI 1.94–3.40, p < 0.05), history of morning sickness (odds ratio: 1.97, 95% CI 1.46–2.65, p < 0.05), and low alcohol intake (odds ratio: 1.94, 95% CI 1.68–2.24, p < 0.05).

Conclusions

Oncologists can use these factors prior to the initiation of a chemotherapy regimen to identify patients at risk for CINV, in order to focus on more comprehensive antiemetic treatment options for those high-risk patients. This may enable better outcomes and avoid complications.

Expert Consensus on Effective Management of Chemotherapy-Induced Nausea and Vomiting: An Indian Perspective

Chemotherapy-induced nausea and vomiting (CINV) is one of the most common and feared side effects in cancer patients undergoing chemotherapy. Scientific evidence proves its detrimental impact on a patient's quality of life (QoL), treatment compliance, and overall healthcare cost. Despite the CINV-management landscape witnessing a radical shift with the introduction of novel, receptor-targeting antiemetic agents, this side effect remains a chink in the armor of a treating oncologist. Though global guidelines acknowledge patient-specific risk factors and chemotherapeutic agent emetogenic potential in CINV control, a "one-fit-for-all" approach cannot be followed across all geographies. Hence, in a pioneering attempt, India-based oncologists conveyed easily implementable, region-specific, consensus-based statements on CINV prevention and management. These statements resulted from integrating the analysis of scientific evidence and guidelines on CINV by the experts, with their clinical experience. The statements will strengthen decision-making abilities of Indian oncologists/clinicians and help in achieving consistency in CINV prevention and management in the country. Furthermore, this document shall lay the foundation for developing robust Indian guidelines for CINV prevention and control.

Gastrointestinal symptoms are associated with trajectories of chemotherapy-induced nausea

PURPOSE

Between 19 and 58% of oncology patients experience chemotherapy-induced nausea (CIN). In a sample of outpatients with breast, gastrointestinal (GI), gynecological, and lung cancer, the study purposes were to evaluate for inter-individual differences in the severity of CIN over two cycles of chemotherapy (CTX) and to determine which demographic and clinical characteristics and GI symptoms were associated with higher initial levels as well as with the trajectories of CIN severity.

METHODS

Patients completed study questionnaires at six time points over two cycles of CTX. These questionnaires provided information on demographic and clinical characteristics, as well as the occurrence of twelve GI symptoms. Hierarchical linear modeling based on full maximum likelihood estimation was performed.

RESULTS

Of the 1251 patients, 47.2% reported CIN. Across two cycles of CTX, lower functional status scores and higher levels of comorbidity were associated with higher initial levels of CIN. Younger age and emetogenicity of the CTX regimen were associated with higher initial levels as well as worse trajectories of CIN. The occurrence of five GI symptoms (i.e., vomiting, lack of appetite, constipation, feeling bloated, and difficulty swallowing) was associated with higher initial levels of CIN. The occurrence of mouth sores was associated with higher initial levels as well as with worst trajectories of CIN.

CONCLUSIONS

This study is the first to identify distinct demographic, clinical, and GI symptom characteristics associated with CIN severity. These findings suggest that the etiology of CIN is complex and may warrant interventions beyond standard antiemetics.

Effect of electrical stimulation for chemotherapy-induced nausea and vomiting in patients with liver cancer

BACKGROUND

This study will be proposed for assessing the effects of electrical stimulation (ES) for chemotherapy-induced nausea and vomiting (CINV) in patients with liver cancer (LC).

METHODS

We will identify the relevant literatures of ES for CINV in patients with LC from following databases: Cochrane Library, PUBMED, EMBASE, Web of Science, the Cumulative Index to Nursing and Allied Health Literature, the Allied and Complementary Medicine Database, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure from inception to the date of literature searched without any language restrictions. Randomized controlled trials and case-control studies on assessing of effects and safety of ES for CINV in patients with LC will be included. Methodological quality for all included studies will be assessed by using Cochrane risk of bias tool. RevMan 5.3 software (Cochrane Community, London, UK) will be used to analyze the data.

RESULTS

This study will summarize current evidence for ES on CINV in patients with LC. Primary outcome includes symptoms severity. Secondary outcomes consist of appetite, performance status, health-related quality of life, and adverse events.

CONCLUSION

The results of this study will provide latest evidence to judge the effects and safety for ES on CINV in patients with LC.

PROSPERO REGISTRATION NUMBER

PROSPERO CRD42019126379.