Enregistrement W4386501692 · doi:10.1001/jamaoncol.2023.2960

The Global, Regional, and National Burden of Adult Lip, Oral, and Pharyngeal Cancer in 204 Countries and Territories

2023· review· en· W4386501692 sur OpenAlexafffund

Amanda Ramos da Cunha, Kelly Compton, Rixing Xu, Rashmi Mishra, Mark Drangsholt, José Leopoldo Ferreira Antunes, Alexander Ross Kerr, Alistair Acheson, Dan Lu, Lindsey E. Wallace, Jonathan Kocarnik, Weijia Fu, Frances Dean, Alyssa Pennini, Hannah Henrikson, Shazia Alam, Emad Ababneh, Sherief Abd‐Elsalam, Meriem Abdoun, Hassan Abidi, Hiwa Abubaker Ali, Eman Abu‐Gharbieh, Tigist Demssew Adane, Isaac Yeboah Addo, Aqeel Ahmad, Sajjad Ahmad, Tarik A. Rashid, Maxwell Akonde, Hanadi Al Hamad, Fares Alahdab, Yousef Alimohamadi, Vahid Alipour, Sadeq Ali Al‐Maweri, Ubai Alsharif, Alireza Ansari‐Moghaddam, Anayochukwu Edward Anyasodor, Jalal Arabloo, Aleksandr Y. Aravkin, Raphael Taiwo Aruleba, Malke Asaad, Tahira Ashraf, Seyyed Shamsadin Athari, Sameh Attia, Sina Azadnajafabad, Mohammadreza Azangou‐Khyavy, Muhammad Badar, Nayereh Baghcheghi, Maciej Banach, Mainak Bardhan, Hiba Jawdat Barqawi, Nasir Zeeshan Bashir, Azadeh Bashiri, Habib Benzian, Eduardo Bernabé, Devidas S. Bhagat, Vijayalakshmi S Bhojaraja, Tone Bjørge, Souad Bouaoud, Dejana Braithwaite, Н. И. Брико, Daniela Călina, Giulia Carreras, Promit Ananyo Chakraborty, Vijay Kumar Chattu, Akhilanand Chaurasia, Mengxuan Chen, William C. Cho, Dinh‐Toi Chu, Isaac Sunday Chukwu, Eunice Chung, Natália Martins, Omid Dadras, Xiaochen Dai, Lalit Dandona, Rakhi Dandona, Parnaz Daneshpajouhnejad, Reza Darvishi Cheshmeh Soltani, Aso Mohammad Darwesh, Sisay Abebe Debela, Meseret Derbew Molla, Fikadu Nugusu Dessalegn, Mostafa Dianatinasab, Lankamo Ena Digesa, Shilpi Gupta Dixit, Abhinav Dixit, Shirin Djalalinia, Iman El Sayed, Maha El Tantawi, Daniel Berhanie Enyew, Daniel Erku, Rana Ezzeddini, Adeniyi Francis Fagbamigbe, Luca Falzone, Getahun Fetensa, Takeshi Fukumoto, Piyada Gaewkhiew, Silvano Gallus, Mesfin Gebrehiwot, Ahmad Ghashghaee, Paramjit Gill, Mahaveer Golechha, Pouya Goleij, Ricardo Santiago Gomez, Giuseppe Gorini, André Luiz Sena Guimarães, Bhawna Gupta, Sapna Gupta, Veer Bala Gupta, Vivek Gupta, Arvin Haj‐Mirzaian, Esam Halboub, Rabih Halwani, Asif Hanif, Ninuk Hariyani, Mehdi Harorani, Hamidreza Hasani, Abbas M. Hassan, Soheil Hassanipour, Mohammed Bheser Hassen, Simon I Hay, Khezar Hayat, Brenda Yuliana Herrera-Serna, Ramesh Holla, Nobuyuki Horita, Mehdi Hosseinzadeh, Salman Hussain, Olayinka Stephen Ilesanmi, Irena Ilić, Milena Ilić, Gaetano Isola, Abhishek Jaiswal, Chinmay Jani, Tahereh Javaheri, Umesh Jayarajah, Shubha Jayaram, Nitin Joseph, Vidya Kadashetti, Eswar Kandaswamy, Shama D. Karanth, Ibraheem M. Karaye, Joonas H. Kauppila, Harkiran Kaur, Mohammad Keykhaei, Yousef Khader, Himanshu Khajuria, Javad Khanali, Mahalaqua Nazli Khatib, Hamid Reza Khayat Kashani, Mohammad Amin Khazeei Tabari, Min Seo Kim, Farzad Kompani, Hamid Reza Koohestani, G Anil Kumar, Om Kurmi, Carlo La Vecchia, Iván Landires, Savita Lasrado, Caterina Ledda, Yo Han Lee, Massimo Libra, Stephen S Lim, Stefan Listl, Platon D Lopukhov, Ahmad R Mafi, Rashidul Alam Mahumud, Ahmad Azam Malik, Manu Raj Mathur, Sazan Qadir Maulud, Jitendra Kumar Meena, Entezar Mehrabi Nasab, Tomislav Meštrović, Reza Mirfakhraie, Awoke Misganaw, Sanjeev Misra, Prasanna Mithra, Yousef Mohammad, Mokhtar Mohammadi, Esmaeil Mohammadi, Ali H. Mokdad, Mohammad Ali Moni, Paula Moraga, Shane D. Morrison, Hamid Reza Mozaffari, Sumaira Mubarik, Christopher J L Murray, Tapas Sadasivan Nair, Sreenivas Narasimha Swamy, Aparna Ichalangod Narayana, Hasan Nassereldine, Zuhair S. Natto, Biswa Prakash Nayak, Șerban Negru, Haruna Asura Nggada, Hasti Nouraei, Virginia Núñez-Samudio, Bogdan Oancea, Andrew T Olagunju, Ahmed Omar Bali, Alicia Padrón‐Monedero, Jagadish Rao Padubidri, Anamika Pandey, Shahina Pardhan, Jay Patel, Raffaele Pezzani, Zahra Zahid Piracha, Navid Rabiee, Venkatraman Radhakrishnan, Raghu Radhakrishnan, Amir M. Rahmani, Vahid Rahmanian, Chythra R Rao, Sowmya J Rao, Goura Kishor Rath, David Laith Rawaf, Salman Rawaf, Reza Rawassizadeh, Mohammad Sadegh Razeghinia, Nazila Rezaei, Negar Rezaei, Nima Rezaei, Aziz Rezapour, Abanoub Riad, Thomas J. Roberts, Esperanza Romero‐Rodríguez, Gholamreza Roshandel, S Manjula, S N Chandan, Basema Saddik, Mohammad Reza Saeb, Umar Saeed, Mohsen Safaei, Maryam Sahebazzamani, Amirhossein Sahebkar, Amir Salek Farrokhi, Abdallah M Samy, Milena M Santric-Milicevic, Brijesh Sathian, Maheswar Satpathy, Mario Šekerija, Subramanian Senthilkumaran, Allen Seylani, Omid Shafaat, Hamid R. Shahsavari, Erfan Shamsoddin, Mequannent Melaku Sharew Sharew, Javad Sharifi‐Rad, Jeevan K. Shetty, K. M. Shivakumar, Parnian Shobeiri, Seyed Afshin Shorofi, Sunil Shrestha, Sudeep K Siddappa Malleshappa, Paramdeep Singh, Jasvinder A. Singh, Garima Singh, Dhirendra Narain Sinha, Yonatan Solomon, Muhammad Suleman, Rizwan Suliankatchi Abdulkader, Yasaman Taheri Abkenar, Iman M. Talaat, Ker‐Kan Tan, Abdelghani Tbakhi, Arulmani Thiyagarajan, Amir Tiyuri, Marcos Roberto Tovani‐Palone, Bhaskaran Unnikrishnan, Bay Vo, Simona Ruxandra Volovăț, Cong Wang, Ronny Westerman, Nuwan Darshana Wickramasinghe, Hong Xiao, Chuanhua Yu, Deniz Yüce, Ismaeel Yunusa, Vesna Zadnik, Iman Zare, Zhi-Jiang Zhang, Mohammad Zoladl, Lisa M Force, Fernando Neves Hugo

Notice bibliographique

RevueJAMA Oncology · 2023

Typereview

Langueen

DomaineMedicine

ThématiqueHead and Neck Cancer Studies

Établissements canadiensMcMaster UniversityUniversity of British Columbia

Organismes subventionnairesDivision of Mathematical SciencesNational Heart, Lung, and Blood InstituteEndocrinology and Metabolism Research Institute, Tehran University of Medical SciencesLeibniz-GemeinschaftNational Health and Medical Research CouncilMedical Research CouncilUniversity of Florida HealthSamsungKing Saud UniversityUniversitätsklinikum HeidelbergMonash University MalaysiaFakultet Medicinskih Nauka, Univerziteta U KragujevcuInstitute for Advanced Studies in Basic SciencesUniversity of ColomboXiamen UniversityNational Institute for Medical Research DevelopmentYasuj University of Medical SciencesUniversity of WashingtonWuhan UniversitySigrid Juséliuksen SäätiöGuilan University of Medical SciencesMasarykova UniverzitaShahid Beheshti University of Medical SciencesHacettepe ÜniversitesiBirjand University of Medical SciencesZhejiang UniversityKerman University of Medical SciencesRajarata University of Sri LankaAin Shams UniversityShiraz University of Medical SciencesCollege of Medicine, Korea UniversityWorld Health OrganizationMazandaran University of Medical SciencesKing Abdulaziz UniversityIsfahan University of Medical SciencesPasteur Institute of IranUniversitatea din BucureștiAlexandria UniversityUniversità degli Studi di PadovaKorea UniversityOulun YliopistoPohang University of Science and TechnologyUniversity of GondarMassachusetts General HospitalLékařská fakulta, Masarykova univerzitaRadboud UniversiteitImperial College LondonShiraz UniversityNational Natural Science Foundation of ChinaMonash UniversityKarolinska InstitutetNational Institute for Health and Care ResearchUniversity of QueenslandAmity UniversityMashhad University of Medical SciencesPublic Health EnglandRoyal College of Surgeons in IrelandUniversity of LeedsPublic Health Foundation of IndiaSt. Jude Children's Research HospitalIndian Council of Medical ResearchNational University of SingaporeUniversity of WarwickCoventry UniversityEuropean CommissionNational Human Genome Research InstituteMacquarie UniversityJSS Academy of Higher Education and ResearchDire Dawa UniversityPolitechnika GdańskaUniversity of ExeterModernaKasturba Medical College, ManipalKermanshah University of Medical SciencesVanderbilt UniversityU.S. Department of Veterans AffairsRafsanjan University of Medical SciencesLouisiana State UniversitySeres TherapeuticsWellcome TrustJohns Hopkins UniversityAmarin CorporationIran University of Medical SciencesBill and Melinda Gates FoundationInstituto de Salud Carlos IIIUniversità degli Studi di MilanoSaveetha Dental CollegeNational Defense Medical CollegeIntuitive SurgicalSveučilište u ZagrebuSocial Science Research CouncilNational Cancer InstituteUniversity of South CarolinaBournemouth UniversityThe Wellcome Trust DBT India AllianceFlinders UniversityUniversidade Federal do Rio Grande do SulHarvard UniversityUniversità di CataniaGolestan University of Medical SciencesTehran University of Medical Sciences and Health ServicesAnglia Ruskin UniversityTehran Heart CenterNational Institutes of HealthUniversity of Veterinary and Animal SciencesFlorida Department of HealthKing Abdullah University of Science and TechnologyDepartment of Biotechnology, Ministry of Science and Technology, IndiaJordan University of Science and TechnologyMcMaster UniversitySchool of Medicine, University of Alabama at BirminghamPlastic Surgery Foundation

Mots-clésMedicineCancerMEDLINEFamily medicineInternal medicine

DOI10.1001/jamaoncol.2023.2960

Résumé

récupéré en direct d'OpenAlex

Importance: Lip, oral, and pharyngeal cancers are important contributors to cancer burden worldwide, and a comprehensive evaluation of their burden globally, regionally, and nationally is crucial for effective policy planning. Objective: To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates. Evidence Review: The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019. Findings: In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia. Conclusions and Relevance: In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002

score de la tête « metaresearch » (Gemma)0,006

Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated

Catégories candidatesaucune

Catégories consensuellesaucune

DomaineSignal candidat: aucune · Signal consensuel: aucune

Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune

GenreSignal candidat: Synthèse · Signal consensuel: Synthèse

Score de désaccord entre enseignants0,055

Score d'incertitude au seuil0,110

Scores du classifieur distillé par catégorie (deux têtes)

Catégorie	Codex	Gemma
Métarecherche	0,002	0,006
Méta-épidémiologie (sens strict)	0,000	0,000
Méta-épidémiologie (sens large)	0,001	0,002
Bibliométrie	0,002	0,005
Études des sciences et des technologies	0,000	0,001
Communication savante	0,002	0,001
Science ouverte	0,001	0,001
Intégrité de la recherche	0,001	0,001
Charge utile insuffisante (le modèle a refusé de juger)	0,006	0,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,076

Tête enseignante GPT0,436

Écart entre enseignants0,359 · la distance entre les deux têtes enseignantes sur ce seul travail

Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.

Devis d'étudeObservationnel

Domainenon disponible

GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations167

Publié2023

Routes d'admission2

Résumé présentoui

Télécharger la notice (JSON)Signaler un problème avec cette notice

Explorer davantage

Même revueJAMA Oncology→Même sujetHead and Neck Cancer Studies→Travaux en français237 207→