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Han CJ, Ning X, Burd CE, Spakowicz DJ, Tounkara F, Kalady MF, Noonan AM, McCabe S, Von Ah D. Chemotoxicity and Associated Risk Factors in Colorectal Cancer: A Systematic Review and Meta-Analysis. Cancers (Basel) 2024; 16:2597. [PMID: 39061235 PMCID: PMC11274507 DOI: 10.3390/cancers16142597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 07/12/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024] Open
Abstract
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.
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Affiliation(s)
- Claire J. Han
- Center for Healthy Aging, Self-Management and Complex Care, College of Nursing, The Ohio State University, Columbus, OH 43210, USA; (S.M.); (D.V.A.)
- The Ohio State University–James: Cancer Treatment and Research Center, Columbus, OH 43210, USA
| | - Xia Ning
- Clinical Informatics and Implementation Science Biomedical Informatics (BMI), Computer Science and Engineering (CSE), College of Engineering, The Ohio State University, Columbus, OH 43210, USA;
| | - Christin E. Burd
- Departments of Molecular Genetics, Cancer Biology and Genetics, The Ohio State University, Columbus, OH 43210, USA;
| | - Daniel J. Spakowicz
- Pelotonia Institute for Immuno-Oncology, Division of Medical Oncology, The Ohio State University, Comprehensive Cancer Center, Columbus, OH 43210, USA;
| | - Fode Tounkara
- Department of Biomedical Informatics, Ohio State University College of Medicine, Columbus, OH 43210, USA;
| | - Matthew F. Kalady
- Division of Colon and Rectal Surgery, The Ohio State University–James: Cancer Treatment and Research Center, Columbus, OH 43210, USA;
| | - Anne M. Noonan
- GI Medical Oncology Selection, The Ohio State University–James: Cancer Treatment and Research Center, Columbus, OH 43210, USA;
| | - Susan McCabe
- Center for Healthy Aging, Self-Management and Complex Care, College of Nursing, The Ohio State University, Columbus, OH 43210, USA; (S.M.); (D.V.A.)
| | - Diane Von Ah
- Center for Healthy Aging, Self-Management and Complex Care, College of Nursing, The Ohio State University, Columbus, OH 43210, USA; (S.M.); (D.V.A.)
- The Ohio State University–James: Cancer Treatment and Research Center, Columbus, OH 43210, USA
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Le Teuff G, Cozic N, Boyer JC, Boige V, Diasio RB, Taieb J, Meulendijks D, Palles C, Schwab M, Deenen M, Largiadèr CR, Marinaki A, Jennings BA, Wettergren Y, Di Paolo A, Gross E, Budai B, Ackland SP, van Kuilenburg ABP, McLeod HL, Milano G, Thomas F, Loriot MA, Kerr D, Schellens JHM, Laurent-Puig P, Shi Q, Pignon JP, Etienne-Grimaldi MC. Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis. Br J Cancer 2024; 130:808-818. [PMID: 38225422 PMCID: PMC10912560 DOI: 10.1038/s41416-023-02517-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/30/2023] [Accepted: 11/23/2023] [Indexed: 01/17/2024] Open
Abstract
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.
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Affiliation(s)
- Gwénaël Le Teuff
- Service de Biostatistique et d'Epidémiologie, Gustave Roussy, Oncostat U1018 INSERM, labeled Ligue Contre le Cancer, Université Paris-Saclay, Villejuif, France.
| | - Nathalie Cozic
- Service de Biostatistique et d'Epidémiologie, Gustave Roussy, Oncostat U1018 INSERM, labeled Ligue Contre le Cancer, Université Paris-Saclay, Villejuif, France
| | | | - Valérie Boige
- Department of cancer medicine, Gustave-Roussy Cancer Campus, Paris-Saclay and Paris-Sud Universities, Villejuif, France
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Equipe Labellisée Ligue Nationale Contre le Cancer, CNRS SNC, 5096, Paris, France
| | - Robert B Diasio
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic Cancer Center, Rochester, MN, USA
| | - Julien Taieb
- Université Paris-Cité, SIRIC CARPEM, Department of Gastroenterology and Digestive Oncology, Georges Pompidou European Hospital, AP-HP, Paris, France
| | - Didier Meulendijks
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Claire Palles
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- Departments of Clinical Pharmacology, and of Biochemistry and Pharmacy, University of Tuebingen, Tuebingen, Germany
- Cluster of Excellence IFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, 72074, Tübingen, Germany
| | - Maarten Deenen
- Department of Clinical Pharmacy, Catharina Hospital, Eindhoven, the Netherlands
| | - Carlo R Largiadèr
- Department of Clinical Chemistry, Bern University Hospital, University of Bern, Inselspital, Bern, Switzerland
| | | | | | | | - Antonello Di Paolo
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eva Gross
- LMU Munich, University Hospital, Campus Grosshadern, Munich, Germany
| | - Barna Budai
- National Institute of Oncology, Budapest, Hungary
| | - Stephen P Ackland
- College of Heath, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, Australia
| | - André B P van Kuilenburg
- Amsterdam UMC, location University of Amsterdam, Laboratory Genetic Metabolic Diseases, Meibergdreef 9, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer Biology and Immunology, Imaging and biomarkers, Amsterdam, The Netherlands
| | - Howard L McLeod
- Intermountain Precision Genomics, Intermountain Healthcare, St George, UT, USA
| | - Gérard Milano
- Oncopharmacology Laboratory, Centre Antoine Lacassagne, Nice, France
| | - Fabienne Thomas
- Institut Claudius Regaud, IUCT-Oncopôle and CRCT, University of Toulouse, Inserm, Toulouse, France
| | - Marie-Anne Loriot
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Equipe Labellisée Ligue Nationale Contre le Cancer, CNRS SNC, 5096, Paris, France
- Hôpital Européen Georges Pompidou, Hôpitaux Universitaires Paris Ouest, Paris, France
| | - David Kerr
- Nuffield Division of Clinical and Laboratory Sciences and University of Oxford, Oxford, UK
| | - Jan H M Schellens
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Pierre Laurent-Puig
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Equipe Labellisée Ligue Nationale Contre le Cancer, CNRS SNC, 5096, Paris, France
- Hôpital Européen Georges Pompidou, Hôpitaux Universitaires Paris Ouest, Paris, France
| | - Qian Shi
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Jean-Pierre Pignon
- Service de Biostatistique et d'Epidémiologie, Gustave Roussy, Oncostat U1018 INSERM, labeled Ligue Contre le Cancer, Université Paris-Saclay, Villejuif, France
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Ruiz Sarrias O, Gónzalez Deza C, Rodríguez Rodríguez J, Arrizibita Iriarte O, Vizcay Atienza A, Zumárraga Lizundia T, Sayar Beristain O, Aldaz Pastor A. Predicting Severe Haematological Toxicity in Gastrointestinal Cancer Patients Undergoing 5-FU-Based Chemotherapy: A Bayesian Network Approach. Cancers (Basel) 2023; 15:4206. [PMID: 37686482 PMCID: PMC10486471 DOI: 10.3390/cancers15174206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/28/2023] [Accepted: 08/16/2023] [Indexed: 09/10/2023] Open
Abstract
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.
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Affiliation(s)
- Oskitz Ruiz Sarrias
- Department of Mathematics and Statistic, NNBi, 31191 Esquiroz, Navarra, Spain; (O.R.S.)
| | - Cristina Gónzalez Deza
- Department of Medical Oncology, Clínica Universidad De Navarra, 31008 Pamplona, Navarra, Spain; (C.G.D.); (J.R.R.); (T.Z.L.)
| | - Javier Rodríguez Rodríguez
- Department of Medical Oncology, Clínica Universidad De Navarra, 31008 Pamplona, Navarra, Spain; (C.G.D.); (J.R.R.); (T.Z.L.)
| | | | - Angel Vizcay Atienza
- Department of Medical Oncology, Clínica Universidad De Navarra, 31008 Pamplona, Navarra, Spain; (C.G.D.); (J.R.R.); (T.Z.L.)
| | - Teresa Zumárraga Lizundia
- Department of Medical Oncology, Clínica Universidad De Navarra, 31008 Pamplona, Navarra, Spain; (C.G.D.); (J.R.R.); (T.Z.L.)
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