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4 results on '"mismatch repair status"'

1. The Association of Mismatch Repair Status with Microscopically Positive (R1) Margins in Stage III Colorectal Cancer: A Retrospective Cohort Study.

Author

Smith HG, Schlesinger NH, Chiranth D, and Qvortrup C

Subjects
Humans, Female, Male, Retrospective Studies, Aged, Survival Rate, Middle Aged, Follow-Up Studies, Prognosis, Aged, 80 and over, Colorectal Neoplasms pathology, Colorectal Neoplasms surgery, DNA Mismatch Repair, Neoplasm Staging, Margins of Excision
Abstract

Background: There is mounting evidence that microscopically positive (R1) margins in patients with colorectal cancer (CRC) may represent a surrogate for aggressive cancer biology rather than technical failure during surgery. However, whether detectable biological differences exist between CRC with R0 and R1 margins is unknown. We sought to investigate whether mismatch repair (MMR) status differs between Stage III CRC with R0 or R1 margins., Methods: Patients treated for Stage III CRC from January 1, 2016 to December 31, 2019 were identified by using the Danish Colorectal Cancer Group database. Patients were stratified according to MMR status (proficient [pMMR] vs. deficient [dMMR]) and margin status. Outcomes of interest included the R1 rate according to MMR and overall survival., Results: A total of 3636 patients were included, of whom 473 (13.0%) had dMMR colorectal cancers. Patients with dMMR cancers were more likely to be elderly, female, and have right-sided cancers. R1 margins were significantly more common in patients with dMMR cancers (20.5% vs. 15.2%, p < 0.001), with the greatest difference seen in the rate of R1 margins related to the primary tumour (8.9% vs. 4.7%) rather than to lymph node metastases (11.6% vs. 10.5%). This association was seen in both right- and left-sided cancers. On multivariable analyses, R1 margins, but not MMR status, were associated with poorer survival, alongside age, pN stage, perineural invasion, and extramural venous invasion., Conclusions: In patients with Stage III CRC, dMMR status is associated with increased risks of R1 margins following potentially curative surgery, supporting the use of neoadjuvant immunotherapy in this patient group., (© 2024. The Author(s).)

Published
2024
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2. Prognostic Role of Mismatch Repair Status, Histotype and High-Risk Pathologic Features in Stage II Small Bowel Adenocarcinomas

Author

Roberto Caronna, Enrico Solcia, Giuseppe Neri, Augusto Orlandi, Michele Martino, Catherine Klersy, Carolina Ciacci, Antonietta D'Errico, Ada Maria Florena, Giovanni Monteleone, Giacomo Caio, Paolo Giuffrida, Gianluca M. Sampietro, Luca Elli, Stefano Ferrero, Maria D'Armiento, G. Solina, Fausto Sessa, Paolo Pedrazzoli, Giuseppe Amodeo, Elena Biletta, Barbara Oreggia, Fabiana Zingone, Deborah Malvi, Claudia Mescoli, Andrea Pietrabissa, Alessandro Vanoli, Camilla Guerini, Giovanni Arpa, Anna D'Odorico, Gabriella Nesi, Massimo Rugge, Fernando Rizzello, Roberto De Giorgio, Federica Grillo, Renato Cannizzaro, Umberto Volta, Livia Biancone, Gilberto Poggioli, Vincenzo Villanacci, Luca Reggiani Bonetti, Maria Cristina Macciomei, Donatella Santini, Sandro Ardizzone, Vincenzo Canzonieri, Rachele Ciccocioppo, Francesco Tonelli, Gino Roberto Corazza, Valeria Barresi, Flavio Caprioli, Roberto Fiocca, Antonio Di Sabatino, Ombretta Luinetti, Giovanni Latella, Paolo Fociani, Marco Paulli, Antonio Calabrò, Antonino Giulio Giannone, Maurizio Vecchi, Renata D'Incà, Aroldo Rizzo, Antonio Ciardi, Marco Vincenzo Lenti, Vanoli A., Grillo F., Guerini C., Neri G., Arpa G., Klersy C., Nesi G., Giuffrida P., Sampietro G., Ardizzone S., Fociani P., Fiocca R., Latella G., Sessa F., D'Errico A., Malvi D., Mescoli C., Rugge M., Ferrero S., Poggioli G., Rizzello F., Macciomei M.C., Santini D., Volta U., De Giorgio R., Caio G., Calabro A., Ciacci C., D'Armiento M., Rizzo A., Solina G., Martino M., Tonelli F., Villanacci V., Cannizzaro R., Canzonieri V., Florena A.M., Biancone L., Monteleone G., Caronna R., Ciardi A., Elli L., Caprioli F., Vecchi M., D'Inca R., Zingone F., D'Odorico A., Lenti M.V., Oreggia B., Reggiani Bonetti L., Giannone A.G., Orlandi A., Barresi V., Ciccocioppo R., Amodeo G., Biletta E., Luinetti O., Pedrazzoli P., Pietrabissa A., Corazza G.R., Solcia E., Paulli M., Di Sabatino A., Vanoli, A., Grillo, F., Guerini, C., Neri, G., Arpa, G., Klersy, C., Nesi, G., Giuffrida, P., Sampietro, G., Ardizzone, S., Fociani, P., Fiocca, R., Latella, G., Sessa, F., D'Errico, A., Malvi, D., Mescoli, C., Rugge, M., Ferrero, S., Poggioli, G., Rizzello, F., Macciomei, M. C., Santini, D., Volta, U., De Giorgio, R., Caio, G., Calabro, A., Ciacci, C., D'Armiento, M., Rizzo, A., Solina, G., Martino, M., Tonelli, F., Villanacci, V., Cannizzaro, R., Canzonieri, V., Florena, A. M., Biancone, L., Monteleone, G., Caronna, R., Ciardi, A., Elli, L., Caprioli, F., Vecchi, M., D'Inca, R., Zingone, F., D'Odorico, A., Lenti, M. V., Oreggia, B., Reggiani Bonetti, L., Giannone, A. G., Orlandi, A., Barresi, V., Ciccocioppo, R., Amodeo, G., Biletta, E., Luinetti, O., Pedrazzoli, P., Pietrabissa, A., Corazza, G. R., Solcia, E., Paulli, M., Di Sabatino, A., Vanoli, Alessandro, Grillo, Federica, Guerini, Camilla, Neri, Giuseppe, Arpa, Giovanni, Klersy, Catherine, Nesi, Gabriella, Giuffrida, Paolo, Sampietro, Gianluca, Ardizzone, Sandro, Fociani, Paolo, Fiocca, Roberto, Latella, Giovanni, Sessa, Fausto, D'Errico, Antonietta, Malvi, Deborah, Mescoli, Claudia, Rugge, Massimo, Ferrero, Stefano, Poggioli, Gilberto, Rizzello, Fernando, Macciomei, Maria C, Santini, Donatella, Volta, Umberto, De Giorgio, Roberto, Caio, Giacomo, Calabrò, Antonio, Ciacci, Carolina, D'Armiento, Maria, Rizzo, Aroldo, Solina, Gaspare, Martino, Michele, Tonelli, Francesco, Villanacci, Vincenzo, Cannizzaro, Renato, Canzonieri, Vincenzo, Florena, Ada Maria, Biancone, Livia, Monteleone, Giovanni, Caronna, Roberto, Ciardi, Antonio, Elli, Luca, Caprioli, Flavio, Vecchi, Maurizio, D'Incà, Renata, Zingone, Fabiana, D'Odorico, Anna, Lenti, Marco Vincenzo, Oreggia, Barbara, Reggiani Bonetti, Luca, Giannone, Antonino Giulio, Orlandi, Augusto, Barresi, Valeria, Ciccocioppo, Rachele, Amodeo, Giuseppe, Biletta, Elena, Luinetti, Ombretta, Pedrazzoli, Paolo, Pietrabissa, Andrea, Corazza, Gino Roberto, Solcia, Enrico, Paulli, Marco, and Di Sabatino, Antonio

Subjects
Male, Oncology, Colorectal cancer, DNA Mismatch Repair, COLORECTAL-CANCER, Settore MED/12, 0302 clinical medicine, PMS2, small bowel adenocarcinoma, Mismatch Repair Endonuclease PMS2, 0303 health sciences, Prognosis, MMR, MutS Homolog 2 Protein, CARCINOMAS, 030220 oncology & carcinogenesis, immunohistochemistry, Mismatch Repair Status, small bowel adenocarcinoma, Female, Microsatellite Instability, DNA mismatch repair, MutL Protein Homolog 1, Colorectal Neoplasms, stage II, medicine.medical_specialty, high-risk pathologic features, Humans, Adenocarcinoma, mismatch repair status, NO, 03 medical and health sciences, small bowel carcinoma, histotype, Internal medicine, Translational Research, medicine, 030304 developmental biology, small bowel adenocarcinomas, business.industry, Cancer, Microsatellite instability, Mismatch Repair Protein, Adenocarcinoma IBD Cancer, medicine.disease, digestive system diseases, MSH6, CONSENSUS, small bowel carcinoma, MMR, immunohistochemistry, Mismatch repair, Small bowel Adenocarcinoma, MSH2, Mismatch repair status, Surgery, business
Abstract

Background Small bowel adenocarcinoma is a relatively rare cancer, often diagnosed in an advanced stage. In localized and resectable disease, surgery alone or in combination with adjuvant chemotherapy is the mainstay of treatment. In the recently published National Comprehensive Cancer Network Clinical Practice guidelines, criteria for selecting patients with stage II small bowel adenocarcinoma to receive adjuvant chemotherapy are provided, and they are mainly extrapolated from studies on colorectal cancer. Patients and Methods In the present study, we aimed to verify whether mismatch repair deficiency phenotype, high-risk pathologic features (including T4, positive resection margins and a low number of lymph nodes harvested), as well as tumor histologic subtype, were associated with cancer-specific survival in 66 stage II non-ampullary small bowel adenocarcinoma patients, collected through the Small Bowel Cancer Italian Consortium. A central histopathology review was performed. Mismatch repair deficiency was tested by immunohistochemistry for MLH1, MSH2, MSH6 and PMS2, and confirmed by polymerase chain reaction for microsatellite instability. Results We identified mismatch repair deficiency, glandular/medullary histologic subtype, and celiac disease as significant predictors of favorable cancer-specific survival using univariable analysis with retained significance in bivariable models adjusted for pT stage. Among the high-risk features, only T4 showed a significant association with an increased risk of death; however, its prognostic value was not independent of mismatch repair status. Conclusions Mismatch repair protein expression, histologic subtype, association with celiac disease, and, in the mismatch repair proficient subset only, T stage, may help identify patients who may benefit from adjuvant chemotherapy. Graphic Abstract

Published
2021

3. Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Author

Jan N. M. IJzermans, Jan Paul Medema, Cornelis J. A. Punt, Marjolein J.E. Greuter, Felice N. van Erning, Martijn G.H. van Oijen, Geraldine R. Vink, Gabrielle Jongeneel, Raju Kandimalla, Gerrit A. Meijer, Ajay Goel, Miriam Koopman, Veerle M.H. Coupé, Luis Bujanda, Remond J.A. Fijneman, Epidemiology and Data Science, APH - Personalized Medicine, Pathology, Internal medicine, Orthopedic Surgery and Sports Medicine, APH - Methodology, CCA - Cancer Treatment and quality of life, Center of Experimental and Molecular Medicine, Radiotherapy, CCA - Imaging and biomarkers, Oncology, APH - Quality of Care, CCA - Cancer Treatment and Quality of Life, and Surgery

Subjects
Oncology, Male, Colorectal cancer, Cost-Benefit Analysis, Economics, Econometrics and Finance (miscellaneous), chemotherapy, survival analysis, fluorouracil, 0302 clinical medicine, Medicine, 030212 general & internal medicine, risk-factors, Netherlands, Aged, 80 and over, Health Care Rationing, Health Policy, Cohort model, Age Factors, Middle Aged, I19, Markov Chains, adjuvant chemotherapy, colon cancer, Chemotherapy, Adjuvant, 030220 oncology & carcinogenesis, Lymphatic Metastasis, Cohort, Colonic Neoplasms, Practice Guidelines as Topic, Biomarker (medicine), Female, Quality-Adjusted Life Years, medicine.medical_specialty, Disease-Free Survival, External validity, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, Biomarkers, Tumor, Humans, mismatch repair status, Survival analysis, Aged, Neoplasm Staging, clinical-trials, Original Paper, therapy, business.industry, Markov cohort model, colorectal-cancer, Reproducibility of Results, Guideline, medicine.disease, mortality, Cancer registry, D61, Neoplasm Recurrence, Local, business, braf
Abstract

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.

Published
2020
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4. Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Author

Medicina, Medikuntza, Jongeneel, Gabrielle, Greuter, Marjolein J. E., Van Erning, Felice N., Koopman, Miriam, Medema, Jan P., Kandimalla, Raju, Goel, Ajay, Bujanda Fernández de Pierola, Luis, Meijer, Gerrit A., Fijneman, Remond J. A., Van Oijen, Martijn G. H., Ijzermans, Jan, Punt, Cornelis J. A., Vink, Geraldine R., Coupé, Veerle M. H., Medicina, Medikuntza, Jongeneel, Gabrielle, Greuter, Marjolein J. E., Van Erning, Felice N., Koopman, Miriam, Medema, Jan P., Kandimalla, Raju, Goel, Ajay, Bujanda Fernández de Pierola, Luis, Meijer, Gerrit A., Fijneman, Remond J. A., Van Oijen, Martijn G. H., Ijzermans, Jan, Punt, Cornelis J. A., Vink, Geraldine R., and Coupé, Veerle M. H.

Abstract

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.

Published
2020

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