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Evidence Synthesis and Classification Branch (ESC)



  1. Lauby-Secretan B, Scoccianti C, Loomis D, Benbrahim-Tallaa L, Bouvard V, Bianchini F, et al.; International Agency for Research on Cancer Handbook Working Group (2015). Breast-cancer screening – viewpoint of the IARC Working Group. N Engl J Med. 372(24):2353–8. https://doi.org/10.1056/NEJMsr1504363 PMID:26039523
  2. Lauby-Secretan B, Scoccianti C, Loomis D, Grosse Y, Bianchini F, Straif K; International Agency for Research on Cancer Handbook Working Group (2016). Body fatness and cancer – Viewpoint of the IARC Working Group. N Engl J Med. 375(8):794–8. https://doi.org/10.1056/NEJMsr1606602 PMID:27557308
  3. Lauby-Secretan B, Vilahur N, Bianchini F, Guha N, Straif K; International Agency for Research on Cancer Handbook Working Group (2018). The IARC perspective on colorectal cancer screening. N Engl J Med. 378(18):1734–40. https://doi.org/10.1056/NEJMsr1714643 PMID:29580179
  4. La Merrill MA, Vandenberg LN, Smith MT, Goodson W, Browne P, Patisaul HB, et al. (2020). Consensus on the key characteristics of endocrine-disrupting chemicals as a basis for hazard identification. Nat Rev Endocrinol. 16(1):45–57. https://doi.org/10.1038/s41574-019-0273-8 PMID:31719706
  5. Samet JM, Chiu WA, Cogliano V, Jinot J, Kriebel D, Lunn RM, et al. (2020). The IARC Monographs: updated procedures for modern and transparent evidence synthesis in cancer hazard identification. J Natl Cancer Inst. 112(1):30–7. https://doi.org/10.1093/jnci/djz169 PMID:31498409
  6. Schubauer-Berigan MK (2020). Hazards at 10 000 m: studies of aircrew and their importance in understanding cancer risks from cosmic radiation and circadian disruption. Occup Environ Med. 77(5):283–4. https://doi.org/10.1136/oemed-2020-106432 PMID:32179634
  7. Smith MT, Guyton KZ, Kleinstreuer N, Borrel A, Cardenas A, Chiu WA, et al. (2020). The key characteristics of carcinogens: relationship to the hallmarks of cancer, relevant biomarkers, and assays to measure them. Cancer Epidemiol Biomarkers Prev. 29(10):1887–903. https://doi.org/10.1158/1055-9965.EPI-19-1346 PMID:32152214
  8. Grosse Y, Lajoie P, Billard M, Krewski D, Rice J, Baan RA, et al. (2019). Development of a database on tumors and tumor sites in humans and in experimental animals for Group 1 agents identified through volume 109 of the IARC Monographs. J Toxicol Environ Health B Crit Rev. 22(7–8):237–43. https://doi.org/10.1080/10937404.2019.1642601 PMID:31612803
  9. Honaryar MK, Lunn RM, Luce D, Ahrens W, ’t Mannetje A, Hansen J, et al. (2019). Welding fumes and lung cancer: a meta-analysis of case-control and cohort studies. Occup Environ Med. 76(6):422–31. https://doi.org/10.1136/oemed-2018-105447 PMID:30948521
  10. Loomis D, Guha N, Kogevinas M, Fontana V, Gennaro V, Kolstad HA, et al. (2019). Cancer mortality in an international cohort of reinforced plastics workers exposed to styrene: a reanalysis. Occup Environ Med. 76(3):157–62. https://doi.org/10.1136/oemed-2018-105131 PMID:29669820
  11. Marques M, Berrington GA, Beland F, Browne P, Demers P, Lachenmeier D, et al.; IARC Monographs Priorities Group (2019). Advisory Group recommendations on priorities for the IARC Monographs. Lancet Oncol. 20(6):763–4. https://doi.org/10.1016/S1470-2045(19)30246-3 PMID:31005580
  12. Mahmood H, Shaban M, Indave BI, Santos-Silva AR, Rajpoot N, Khurram SA (2020). Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: a systematic review. Oral Oncol. 110:104885. https://doi.org/10.1016/j.oraloncology.2020.104885 PMID:32674040
  13. Salgado R, Bellizzi AM, Rimm D, Bartlett JMS, Nielsen T, Holger M, et al. (2020). How current assay approval policies are leading to unintended imprecision medicine. Lancet Oncol. 21(11):1399–401. https://doi.org/10.1016/S1470-2045(20)30592-1 PMID:33098760
  14. Huybrechts I, Zouiouich S, Loobuyck A, Vandenbulcke Z, Vogtmann E, Pisanu S, et al. (2020). The human microbiome in relation to cancer risk: a systematic review of epidemiologic studies. Cancer Epidemiol Biomarkers Prev. 29(10):1856–68. https://doi.org/10.1158/1055-9965.EPI-20-0288 PMID:32727720
  15. Quezada-Marín JI, Lam AK, Ochiai A, Odze RD, Washington KM, Fukayama M, et al. (2020). Gastrointestinal tissue-based molecular biomarkers: a practical categorisation based on the 2019 World Health Organization classification of epithelial digestive tumours. Histopathology. 77(3):340–50. https://doi.org/10.1111/his.14120 PMID:32320495
  16. Gonzalez-Ericsson PI, Stovgaard ES, Sua LF, Reisenbichler E, Kos Z, Carter JM, et al.; International Immuno-Oncology Biomarker Working Group (2020). The path to a better biomarker: application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice. J Pathol. 250(5):667–84. https://doi.org/10.1002/path.5406 PMID:32129476
  17. Tan PH, Ellis I, Allison K, Brogi E, Fox SB, Lakhani S, et al.; WHO Classification of Tumours Editorial Board (2020). The 2019 World Health Organization classification of tumours of the breast. Histopathology. 77(2):181–5. https://doi.org/10.1111/his.14091 PMID:32056259
  18. Louis DN, Wesseling P, Aldape K, Brat DJ, Capper D, Cree IA, et al. (2020). cIMPACT-NOW update 6: new entity and diagnostic principle recommendations of the cIMPACT-Utrecht meeting on future CNS tumor classification and grading. Brain Pathol. 30(4):844–56. https://doi.org/10.1111/bpa.12832 PMID:32307792
  19. Uttley L, Indave BI, Hyde C, White V, Lokuhetty D, Cree I (2020). Invited commentary – WHO Classification of Tumours: How should tumors be classified? Expert consensus, systematic reviews or both? Int J Cancer. 146(12):3516–21. https://doi.org/10.1002/ijc.32975 PMID:32170735


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