Predictive factors of severe early treatment-related toxicity in patients receiving first-line treatment for metastatic colorectal cancer: Pooled analysis of 2190 patients enrolled in Fédération Francophone de Cancérologie Digestive (FFCD) trials

The Prevalence of 5-Fluorouracil and Capecitabine Cardiotoxicity: A Systematic Review and Meta-Analysis

Background

The incidence of cardiotoxicity events in patients who use 5-fluorouracil (5-FU) and capecitabine monotherapy remains unclear since previous studies reported the prevalence in patients who used combination regimens. We aimed to systematically review and meta-analyze the incidence of cardiotoxicity in fluorouracil and capecitabine monotherapy users.

Methods

The study protocol was registered with PROSPERO (CRD42023441627). Systematic searches were conducted in five databases (CINAHL, OpenGrey, PubMed, ScienceDirect, and Scopus). The Cochrane Risk-of-Bias tool and the Risk Of Bias In Non-randomized Studies were used to evaluate the risk of bias. Pooled prevalence and 95% confidence interval (CI) were calculated using the DerSimonian-Laird random effect models. The funnel plot was used to assess the publication bias.

Results

Eighty studies were included. There were 24 randomized controlled trials (RCTs) with low to high risk of bias and 56 non-RCTs with critical risk of bias. The pooled prevalence of cardiotoxicity from 5-FU was 3.5% (95% CI: 2.7 - 4.2; P < 0.001; I2 = 73.86%). The pooled prevalence of cardiotoxicity in capecitabine users was 2.8% (95% CI: 1.6 - 4.0; P < 0.001; I2 = 72.62%).

Conclusions

The prevalence of cardiotoxicity from 5-FU and capecitabine was classified as common. Cardiotoxicity may have not been associated with the cumulative dose of 5-FU or capecitabine.

Chemotoxicity and Associated Risk Factors in Colorectal Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Colorectal cancer (CRC) patients experience multiple types of chemotoxicity affecting treatment compliance, survival, and quality of life (QOL). Prior research shows clinician-reported chemotoxicity (i.e., grading scales or diagnostic codes) predicts rehospitalization and cancer survival. However, a comprehensive synthesis of clinician-reported chemotoxicity is still lacking.

OBJECTIVES

We conducted a systematic review and meta-analysis to determine chemotoxicity's prevalence and risk factors in CRC.

METHODS

A systematic search from 2009 to 2024 yielded 30 studies for review, with 25 included in the meta-analysis.

RESULTS

Pooled prevalences of overall, non-hematological, and hematological moderate-to-severe toxicities were 45.7%, 39.2%, and 25.3%, respectively. The most common clinician-reported chemotoxicities were gastrointestinal (GI) toxicity (22.9%) and neuropathy or neutropenia (17.9%). Significant risk factors at baseline were malnutritional status, frailty, impaired immune or hepato-renal functions, short telomere lengths, low gut lactobacillus levels, age, female sex, aggressive chemotherapy, and low QOL. Age was associated with neutropenia (β: -1.44) and GI toxicity (β:1.85) (p-values < 0.01). Older adults (>65 y.o.) had higher prevalences of overall (OR: 1.14) and GI (OR: 1.65) toxicities, but a lower prevalence of neutropenia (OR: 0.65) than younger adults (p-values < 0.05).

CONCLUSIONS

Our findings highlight the importance of closely monitoring and managing chemotoxicity in CRC patients receiving chemotherapy.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis

BACKGROUND

Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity.

METHODS

Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC).

RESULTS

Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants.

CONCLUSIONS

FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

Predicting Severe Haematological Toxicity in Gastrointestinal Cancer Patients Undergoing 5-FU-Based Chemotherapy: A Bayesian Network Approach

PURPOSE

Severe toxicity is reported in about 30% of gastrointestinal cancer patients receiving 5-Fluorouracil (5-FU)-based chemotherapy. To date, limited tools exist to identify at risk patients in this setting. The objective of this study was to address this need by designing a predictive model using a Bayesian network, a probabilistic graphical model offering robust, explainable predictions.

METHODS

We utilized a dataset of 267 gastrointestinal cancer patients, conducting preprocessing, and splitting it into TRAIN and TEST sets (80%:20% ratio). The RandomForest algorithm assessed variable importance based on MeanDecreaseGini coefficient. The bnlearn R library helped design a Bayesian network model using a 10-fold cross-validation on the TRAIN set and the aic-cg method for network structure optimization. The model's performance was gauged based on accuracy, sensitivity, and specificity, using cross-validation on the TRAIN set and independent validation on the TEST set.

RESULTS

The model demonstrated satisfactory performance with an average accuracy of 0.85 (±0.05) and 0.80 on TRAIN and TEST datasets, respectively. The sensitivity and specificity were 0.82 (±0.14) and 0.87 (±0.07) for the TRAIN dataset, and 0.71 and 0.83 for the TEST dataset, respectively. A user-friendly tool was developed for clinical implementation.

CONCLUSIONS

Despite several limitations, our Bayesian network model demonstrated a high level of accuracy in predicting the risk of developing severe haematological toxicity in gastrointestinal cancer patients receiving 5-FU-based chemotherapy. Future research should aim at model validation in larger cohorts of patients and different clinical settings.