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374 results on '"Valero, Cristina"'

1. Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data

Author

Yoo, Seong-Keun, Fitzgerald, Conall W., Cho, Byuri Angela, Fitzgerald, Bailey G., Han, Catherine, Koh, Elizabeth S., Pandey, Abhinav, Sfreddo, Hannah, Crowley, Fionnuala, Korostin, Michelle Rudshteyn, Debnath, Neha, Leyfman, Yan, Valero, Cristina, Lee, Mark, Vos, Joris L., Lee, Andrew Sangho, Zhao, Karena, Lam, Stanley, Olumuyide, Ezekiel, Kuo, Fengshen, Wilson, Eric A., Hamon, Pauline, Hennequin, Clotilde, Saffern, Miriam, Vuong, Lynda, Hakimi, A. Ari, Brown, Brian, Merad, Miriam, Gnjatic, Sacha, Bhardwaj, Nina, Galsky, Matthew D., Schadt, Eric E., Samstein, Robert M., Marron, Thomas U., Gönen, Mithat, Morris, Luc G. T., and Chowell, Diego

Published
2025
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17. Functional landscapes of POLE and POLD1 mutations in checkpoint blockade-dependent antitumor immunity

Author

Ma, Xiaoxiao, Riaz, Nadeem, Samstein, Robert M., Lee, Mark, Makarov, Vladimir, Valero, Cristina, Chowell, Diego, Kuo, Fengshen, Hoen, Douglas, Fitzgerald, Conall W. R., Jiang, Hui, Alektiar, Jonathan, Alban, Tyler J., Juric, Ivan, Parthasarathy, Prerana Bangalore, Zhao, Yu, Sabio, Erich Y., Verma, Richa, Srivastava, Raghvendra M., Vuong, Lynda, Yang, Wei, Zhang, Xiao, Wang, Jingming, Chu, Lawrence K., Wang, Stephen L., Kelly, Daniel W., Pei, Xin, Chen, Jiapeng, Yaeger, Rona, Zamarin, Dmitriy, Zehir, Ahmet, Gönen, Mithat, Morris, Luc G. T., and Chan, Timothy A.

Published
2022
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18. Skull base surgery for malignant tumors: The 2nd international collaborative study (1995–2015).

Author

Shah, Jatin P., Levyn, Helena, Valero, Cristina, Adilbay, Dauren, Eagan, Alana, Zheng, Junting, Gonen, Mithat, Cohen, Marc, Patel, Snehal, Ganly, Ian, Pai, Prathamesh, Castelnuovo, Paolo, Gao, Fang Ju, Piazza, Cesare, Nicolai, Piero, Panizza, Ben, Bowman, James, Barnett, Catherine, Kowalski, Luiz P., and Toledo, Ronaldo

Subjects
SKULL base, SURVIVAL rate, SKULL surgery, SKULL tumors, ENDOSCOPIC surgery
Abstract

Background: The current study presents the effort of a global collaborative group to review the management and outcomes of malignant tumors of the skull base worldwide. Patients and methods: A total of 28 institutions contributed data on 3061 patients. Analysis evaluated clinical variables, survival outcomes, and multivariable factors associated with outcomes. Results: The median age was 56 years (IQR 44–67). The open surgical approach was used in 55% (n = 1680) of cases, endoscopic resection was performed in 36% (n = 1087), and the combined approach in 9.6% (n = 294). With a median follow‐up of 7.1 years, the 5‐year OS DSS and RFS were 65%, 71.7% and 53%, respectively. On multivariable analysis, older age, comorbidities, histology, dural/intracranial involvement, positive margins, advanced stage, and primary site were independent prognostic factors for OS, DSS, and RFS. Adjuvant RT was a protective prognostic factor. Conclusion: The progress across various disciplines may have contributed to improved OS and DSS in this study compared to previous reports. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Clinical-genomic determinants of immune checkpoint blockade response in head and neck squamous cell carcinoma

Author

Valero, Cristina, Golkaram, Mahdi, Vos, Joris L., Xu, Bin, Fitzgerald, Conall, Lee, Mark, Kaplan, Shannon, Han, Catherine Y., Pei, Xin, Sarkar, Reith, Boe, Lillian A., Pandey, Abhinav, Koh, Elizabeth S., Zuur, Charlotte L., Pawlowski, David B. SoliTraci, Liu, Li, Ho, Alan L., Chowell, Diego, Riaz, Nadeem, Chan, Timothy A., and Morris, Luc G.T.

Subjects
Immune response -- Genetic aspects -- Health aspects, Squamous cell carcinoma -- Genetic aspects -- Drug therapy -- Patient outcomes, Monoclonal antibodies -- Patient outcomes, Head and neck cancer -- Patient outcomes -- Genetic aspects -- Drug therapy, Health care industry
Abstract

BACKGROUND. Recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is generally an incurable disease, with patients experiencing median survival of under 10 months and significant morbidity. While immune checkpoint blockade (ICB) drugs are effective in approximately 20% of patients, the remaining experience limited clinical benefit and are exposed to potential adverse effects and financial costs. Clinically approved biomarkers, such as tumor mutational burden (TMB), have a modest predictive value in HNSCC. METHODS. We analyzed clinical and genomic features, generated using whole-exome sequencing, in 133 ICB-treated patients with R/M HNSCC, of whom 69 had virus-associated and 64 had non-virus-associated tumors. RESULTS. Hierarchical clustering of genomic data revealed 6 molecular subtypes characterized by a wide range of objective response rates and survival after ICB therapy. The prognostic importance of these 6 subtypes was validated in an external cohort. A random forest-based predictive model, using several clinical and genomic features, predicted progression-free survival (PFS), overall survival (OS), and response with greater accuracy than did a model based on TMB alone. Recursive partitioning analysis identified 3 features (systemic inflammatory response index, TMB, and smoking signature) that classified patients into risk groups with accurate discrimination of PFS and OS. CONCLUSION. These findings shed light on the immunogenomic characteristics of HNSCC tumors that drive differential responses to ICB and identify a clinical-genomic classifier that outperformed the current clinically approved biomarker of TMB. This validated predictive tool may help with clinical risk stratification in patients with R/M HNSCC for whom ICB is being considered. FUNDING. Fundacion Alfonso Martin Escudero, NIH R01 DE027738, US Department of Defense CA210784, The Geoffrey Beene Cancer Research Center, The MSKCC Population Science Research Program, the Jayme Flowers Fund, the Sebastian Nativo Fund, and the NIH/NCI Cancer Center Support Grant P30 CA008748., Introduction Head and neck squamous cell carcinoma (HNSCC) describes a group of tumors that arise from the mucosal lining of the head and neck--specifically, the oral cavity, oropharynx, larynx, hypopharynx, [...]

Published
2023
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21. Improved prediction of immune checkpoint blockade efficacy across multiple cancer types

Author

Chowell, Diego, Yoo, Seong-Keun, Valero, Cristina, Pastore, Alessandro, Krishna, Chirag, Lee, Mark, Hoen, Douglas, Shi, Hongyu, Kelly, Daniel W., Patel, Neal, Makarov, Vladimir, Ma, Xiaoxiao, Vuong, Lynda, Sabio, Erich Y., Weiss, Kate, Kuo, Fengshen, Lenz, Tobias L., Samstein, Robert M., Riaz, Nadeem, Adusumilli, Prasad S., Balachandran, Vinod P., Plitas, George, Ari Hakimi, A., Abdel-Wahab, Omar, Shoushtari, Alexander N., Postow, Michael A., Motzer, Robert J., Ladanyi, Marc, Zehir, Ahmet, Berger, Michael F., Gönen, Mithat, Morris, Luc G. T., Weinhold, Nils, and Chan, Timothy A.

Published
2022
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22. Real-World Treatment Patterns and Clinical Outcomes of Baricitinib in Rheumatoid Arthritis Patients in Spain: Results of a Multicenter, Observational Study in Routine Clinical Practice (The ORBIT-RA Study)

Author

Hernández-Cruz, Blanca, Rosas, José, Díaz-Torné, César, Belzunegui, Joaquín, García-Vicuña, Rosario, Inciarte-Mundo, José, Pons, Ana, Millán, Ana M., Jeria-Navarro, Sicylle, Valero, Jesús A., García-Castañeda, Noelia, Valero, Cristina, Llorente, Irene, Calvo, Alberto, Díaz-Cerezo, Silvia, and Núñez, Mercedes

Published
2022
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30. IL-6 serum levels predict severity and response to tocilizumab in COVID-19: An observational study

Author

Alvarado, Teresa, Martínez, Pablo, Javier de la Cuerda Llorente, Francisco, Arco, Carmen del, Aguilar, Juan Mariano, Villalba, Natalia, Negro, Mónica, Contreras, Elvira, Rey, Ana del, Santiago, Cristina, Junquera, Manuel, Caminero, Raquel, Val, Francisco Javier, González, Sonia, Caño, Marta, López, Isabel, von Wernitz, Andrés, Retana, Bárbara, Guerra, Iñigo, Sorando, Jorge, Chao, Lydia, Cárdenas, María José, Espiga, Verónica, Chicharro, Pablo, Rodríguez, Pedro, Alday, Iñigo Hernando, Sampedro, Miguel, Prada, Jorge, Aldama, Eukene Rojo, Real, Yolanda, Caldas, María, Casabona, Sergio, Lanas-Gimeno, Aitor, Camara, Rafael de la, Alvárez, Angela Figuera, Aguadol, Beatriz, Morell, Alberto, Ramírez, Esther, Zurriaga, Amparo Ibáñez, Abanades, María Pérez, García, Silvia Ruiz, Aranda, Tomás Gallego, Ruiz, María, Nieto, Concepción Martínez, Serra, José María, Sánchez-Madrid, Francisco, Muñoz-Calleja, Cecilia, Alfranca, Arantzazu, Aspa, Javier, Marcos-Jiménez, Ana, Sánchez-Alonso, Santiago, Alcaraz-Serna, Ana, Mateu-Albero, Tamara, Sánchez-Cerrillo, Ildefonso, Esparcia, Laura, Martínez-Fleta, Pedro, López-Sanz, Celia, Gabrie, Ligia, Guerola, Luciana del Campo, Fernández, Elena, Calzada, M<ce:sup loc='post"><ce:underline>a</ce:underline></ce:sup> José, Tejedor, Reyes, Canabal, Alfonso, Albert, Patricia, Rodríguez-Serrano, Diego A., Iglesias, Judit, Suarez, Fernando, Sánchez, Juan Antonio, Abad, Beatriz, Suarez, Carmen, Santos, Ignacio de los, Galván-Román, José María, Roy, Emilia, Rodríguez-Cortes, Pablo, García-Fraile, Lucio, Sanz, Jesus, Sanchez, Eduardo, Moldenhauer, Fernando, Casado, Pedro, Curbelo, Jose, Gutierrez, Angela, Bautista, Azucena, Giménez, Nuria Ruiz, Fernandez, Angelica, Parra, Pedro, Moyano, Berta, Barrios, Ana, Real de Asua, Diego, Sanchez, Beatriz, Saez, Carmen, Ciudad, Marianela, Navas, Desiré, Domingo, Laura Cardeñoso, Torresano, María del Carmen Cuevas, García, Diego Domingo, Cavero, Teresa Alarcón, Blanco, Alicia García, Ramírez, Alexandra Martín, Semiglia Chong, María Auxiliadora, Cobos, Ainhoa Gutiérrez, Zurita Cruz, Nelly Daniela, Fraile Torres, Arturo Manuel, Sanchez-Gonzalez, Carmen, Perpén, Antonio Fernádez, Pérez, Carolina Díaz, Ancochea, Julio, Alonso, Tamara, Landete, Pedro, Soriano, Joan, Cisneros, Carolina, Castillo, Elena García, García Pérez, Francisco Javier, Girón, Rosa María, Marcos, Celeste, Zamora, Enrique, García, Patricia García, Castañeda, Santos, García-Vicuña, Rosario, González-Álvaro, Isidoro, Rodríguez-García, Sebastián, Fernández-Díaz, Carlos, Cubas, Irene Llorente, Tomero, Eva G., Castañeda, Noelia García, Ortiz, Ana M<ce:sup loc='post"><ce:underline>a</ce:underline></ce:sup>, Valero, Cristina, Uriarte, Miren, Montes, Nuria, Rodríguez-García, Sebastián C., Roy-Vallejo, Emilia, del Campo Guerola, Luciana, Suárez-Fernández, Carmen, del Arco, Carmen, de los Santos, Ignacio, de la Cámara, Rafael, Soriano, Joan B., Martín-Gayo, Enrique, Fraile Torres, Arturo, and Cardeñoso, Laura

Published
2021
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31. 'CREA': An Inquiry-Based Methodology to Teach Robotics to Children

Author

Blancas, Maria, Valero, Cristina, Mura, Anna, Vouloutsi, Vasiliki, Verschure, Paul F. M. J., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Merdan, Munir, editor, Lepuschitz, Wilfried, editor, Koppensteiner, Gottfried, editor, Balogh, Richard, editor, and Obdržálek, David, editor

Published
2020
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35. Trends in hospitalisation for urinary tract infection in adults aged 18–65 by sex in Spain: 2000 to 2015

Author

Redondo-Sánchez, Jesús, primary, Rodríguez-Barrientos, Ricardo, additional, de-Hoyos-Alonso, Mª del Canto, additional, Muntañola-Valero, Cristina, additional, Almendro Martínez, Isabel, additional, Peñalver-Argüeso, Belén, additional, Fernández-Escobar, Carlos, additional, Gil-de Miguel, Ángel, additional, and del Cura-González, Isabel, additional

Published
2024
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36. A Prospective Double-Blinded Comparison of Reflectance Confocal Microscopy with Conventional Histopathology for In Vivo Assessment in Oral Cancer

Author

Zanoni, Daniella K., primary, Demétrio De Souza França, Paula, additional, Valero, Cristina, additional, Peterson, Gary, additional, Ardigo, Marco, additional, Ghossein, Ronald, additional, Dusza, Stephen W., additional, Matsuura, Danielli, additional, Scholfield, Daniel W., additional, Adilbay, Dauren, additional, Montero, Pablo H., additional, Migliacci, Jocelyn, additional, Pillarsetty, Naga Vara Kishore, additional, Kose, Kivanc, additional, Ganly, Ian, additional, Rajadhyaksha, Milind, additional, and Patel, Snehal G., additional

Published
2024
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37. Correction to: Real-world Treatment Patterns and Clinical Outcomes of Baricitinib in Rheumatoid Arthritis patients in Spain: Results of a multicenter, observational study in routine clinical practice (The ORBIT-RA Study)

Author

Hernández-Cruz, Blanca, Rosas, José, Díaz-Torné, César, Belzunegui, Joaquín, García-Vicuña, Rosario, Inciarte-Mundo, José, Pons, Ana, Millán, Ana M., Jeria-Navarro, Sicylle, Valero, Jesús A., García-Castañeda, Noelia, Valero, Cristina, Llorente, Irene, Calvo, Alberto, Díaz-Cerezo, Silvia, and Núñez, Mercedes

Published
2022
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38. The association between tumor mutational burden and prognosis is dependent on treatment context

Author

Valero, Cristina, Lee, Mark, Hoen, Douglas, Wang, Jingming, Nadeem, Zaineb, Patel, Neal, Postow, Michael A., Shoushtari, Alexander N., Plitas, George, Balachandran, Vinod P., Smith, J. Joshua, Crago, Aimee M., Long Roche, Kara C., Kelly, Daniel W., Samstein, Robert M., Rana, Satshil, Ganly, Ian, Wong, Richard J., Hakimi, A. Ari, Berger, Michael F., Zehir, Ahmet, Solit, David B., Ladanyi, Marc, Riaz, Nadeem, Chan, Timothy A., Seshan, Venkatraman E., and Morris, Luc G. T.

Published
2021
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39. Pretreatment neutrophil-to-lymphocyte ratio and mutational burden as biomarkers of tumor response to immune checkpoint inhibitors

Author

Valero, Cristina, Lee, Mark, Hoen, Douglas, Weiss, Kate, Kelly, Daniel W., Adusumilli, Prasad S., Paik, Paul K., Plitas, George, Ladanyi, Marc, Postow, Michael A., Ariyan, Charlotte E., Shoushtari, Alexander N., Balachandran, Vinod P., Hakimi, A. Ari, Crago, Aimee M., Long Roche, Kara C., Smith, J. Joshua, Ganly, Ian, Wong, Richard J., Patel, Snehal G., Shah, Jatin P., Lee, Nancy Y., Riaz, Nadeem, Wang, Jingming, Zehir, Ahmet, Berger, Michael F., Chan, Timothy A., Seshan, Venkatraman E., and Morris, Luc G. T.

Published
2021
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40. Educational Robotics

Author

Blancas, Maria, primary, Valero, Cristina, additional, Vouloutsi, Vasiliki, additional, Mura, Anna, additional, and Verschure, Paul F. M. J., additional

Published
2021
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43. Development and validation of a novel TNM staging N‐classification of oral cavity squamous cell carcinoma

Author

de Almeida, John R., primary, Su, Jie Susie, additional, Kolarski, Mirko Manojlovic, additional, Truong, Tra, additional, Weinreb, Ilan, additional, Perez‐Ordonez, Bayardo, additional, Smith, Stephen M., additional, Hosni, Ali, additional, Patel, Snehal, additional, Valero, Cristina, additional, Xu, Bin, additional, Ghossein, Ronald, additional, Katabi, Nora, additional, Clark, Jonathan, additional, Low, Tsu‐Hui (Hubert), additional, Gupta, Ruta, additional, Graboyes, Evan M., additional, Davies, Joel, additional, Richardson, Mary, additional, Pasham, Vishu, additional, Jester, Rachel, additional, Goldstein, David P., additional, Huang, Shao Hui, additional, Xu, Wei, additional, and O’Sullivan, Brian, additional

Published
2023
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46. Development and validation of a novel TNM staging N‐classification of oral cavity squamous cell carcinoma.

Author

de Almeida, John R., Su, Jie Susie, Kolarski, Mirko Manojlovic, Truong, Tra, Weinreb, Ilan, Perez‐Ordonez, Bayardo, Smith, Stephen M., Hosni, Ali, Patel, Snehal, Valero, Cristina, Xu, Bin, Ghossein, Ronald, Katabi, Nora, Clark, Jonathan, Low, Tsu‐Hui, Gupta, Ruta, Graboyes, Evan M., Davies, Joel, Richardson, Mary, and Pasham, Vishu

Abstract

Background: For oral cavity squamous cell carcinoma (OSCC), extent of extranodal extension (ENE) (minor, ≤2 mm; major, >2 mm) is differentially prognostic, whereas limitations exist with the 8th edition of American Joint Committee on Cancer/International Union Against Cancer TNM N‐classification (TNM‐8‐N). Methods: Resected OSCC patients at four centers were included and extent of ENE was recorded. Thresholds for optimal overall survival (OS) discrimination of lymph node (LN) features were established. After dividing into training and validation sets, two new N‐classifications were created using 1) recursive partitioning analysis (RPA), and 2) adjusted hazard ratios (aHRs) and were ranked against TNM‐8‐N and two published proposals. Results: A total of 1460 patients were included (pN0: 696; pN+: 764). Of the pN+ cases, 135 (18%) had bilateral/contralateral LNs; 126 (17%) and 244 (32%) had minor and major ENE, and two (0.3%) had LN(s) >6 cm without ENE (N3a). LN number (1 and >1 vs. 0: aHRs, 1.92 [95% confidence interval (CI), 1.44–2.55] and 3.21 [95% CI, 2.44–4.22]), size (>3 vs. ≤3 cm: aHR, 1.88 [95% CI, 1.44–2.45]), and ENE extent (major vs. minor: aHR, 1.40 [95% CI, 1.05–1.87]) were associated with OS, whereas presence of contralateral LNs was not (aHR, 1.05 [95% CI, 0.81–1.36]). The aHR proposal provided optimal performance with these changes to TNM‐8‐N: 1) stratification of ENE extent, 2) elimination of N2c and 6‐cm threshold, and 3) stratification of N2b by 3 cm threshold. Conclusion: A new N‐classification improved staging performance compared to TNM‐8‐N, by stratifying by ENE extent, eliminating the old N2c category and the 6 cm threshold, and by stratifying multiple nodes by size. There are several limitations in the most recent TNM N classification system including categories with small sample size and categories that have limited prognostic value. The authors proposed and validated a new N classification system that overcomes these limitations and outperforms the previous iteration of TNM. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Neutrophil to Lymphocyte Ratio in Oropharyngeal Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis †

Author

MS Hoofd-Hals Chirurgische Oncologie, Cancer, Rodrigo, Juan P., Sánchez-Canteli, Mario, Triantafyllou, Asterios, de Bree, Remco, Mäkitie, Antti A., Franchi, Alessandro, Hellquist, Henrik, Saba, Nabil F., Stenman, Göran, Takes, Robert P., Valero, Cristina, Zidar, Nina, Ferlito, Alfio, MS Hoofd-Hals Chirurgische Oncologie, Cancer, Rodrigo, Juan P., Sánchez-Canteli, Mario, Triantafyllou, Asterios, de Bree, Remco, Mäkitie, Antti A., Franchi, Alessandro, Hellquist, Henrik, Saba, Nabil F., Stenman, Göran, Takes, Robert P., Valero, Cristina, Zidar, Nina, and Ferlito, Alfio

Published
2023

50. Validation of a Machine Learning Model to Predict Immunotherapy Response in Head and Neck Squamous Cell Carcinoma.

Author

Lee, Andrew Sangho, Valero, Cristina, Yoo, Seong-keun, Vos, Joris L., Chowell, Diego, and Morris, Luc G. T.

Subjects
*CONFIDENCE intervals, *IMMUNE checkpoint inhibitors, *RESEARCH methodology evaluation, *RESEARCH methodology, *MACHINE learning, *HEAD & neck cancer, *RANDOM forest algorithms, *TREATMENT effectiveness, *DESCRIPTIVE statistics, *RESEARCH funding, *RECEIVER operating characteristic curves, *PROGRESSION-free survival, *SQUAMOUS cell carcinoma, *IMMUNOTHERAPY
Abstract

Simple Summary: Recurrent and/or metastatic head and neck squamous-cell carcinoma (R/M HNSCC) is a clinically challenging disease with a poor prognosis. Despite advances in survival through the use of immune-checkpoint blockade, only a minority of patients experience benefit from such treatments, and it is difficult to identify the patients most likely to benefit. Machine learning approaches integrating clinical and genomic data can predict response to immune-checkpoint blockade across all cancers; however, the performance of this model in HNSCC has not been examined. Here, we validate this previously described immune-checkpoint blockade response prediction model in R/M HNSCC patients. This model was able to predict response as well as overall survival following immune-checkpoint blockade in patients with R/M HNSCC. Further investigation will be needed to further delineate the importance of HNSCC-specific features. Head and neck squamous-cell carcinoma (HNSCC) is a disease with a generally poor prognosis; half of treated patients eventually develop recurrent and/or metastatic (R/M) disease. Patients with R/M HNSCC generally have incurable disease with a median survival of 10 to 15 months. Although immune-checkpoint blockade (ICB) has improved outcomes in patients with R/M HNSCC, identifying patients who are likely to benefit from ICB remains a challenge. Biomarkers in current clinical use include tumor mutational burden and immunohistochemistry for programmed death-ligand 1, both of which have only modest predictive power. Machine learning (ML) has the potential to aid in clinical decision-making as an approach to estimate a tumor's likelihood of response or a patient's likelihood of experiencing clinical benefit from therapies such as ICB. Previously, we described a random forest ML model that had value in predicting ICB response using 11 or 16 clinical, laboratory, and genomic features in a pan-cancer development cohort. However, its applicability to certain cancer types, such as HNSCC, has been unknown, due to a lack of cancer-type-specific validation. Here, we present the first validation of a random forest ML tool to predict the likelihood of ICB response in patients with R/M HNSCC. The tool had adequate predictive power for tumor response (area under the receiver operating characteristic curve = 0.65) and was able to stratify patients by overall (HR = 0.53 [95% CI 0.29–0.99], p = 0.045) and progression-free (HR = 0.49 [95% CI 0.27–0.87], p = 0.016) survival. The overall accuracy was 0.72. Our study validates an ML predictor in HNSCC, demonstrating promising performance in a novel cohort of patients. Further studies are needed to validate the generalizability of this algorithm in larger patient samples from additional multi-institutional contexts. [ABSTRACT FROM AUTHOR]

Published
2024
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