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Akbari, Narjes, Safdari, Reza, Mansourian, Arash, Ehtesham, Hamideh. (1401). Development of a National Consensus Minimum Data Set for the Diagnosis and Treatment of Oral Cancer: Towards Precision Management. سامانه مدیریت نشریات علمی, 13(2), 343-351. doi: 10.30476/mejc.2021.87375.1414
Narjes Akbari; Reza Safdari; Arash Mansourian; Hamideh Ehtesham. "Development of a National Consensus Minimum Data Set for the Diagnosis and Treatment of Oral Cancer: Towards Precision Management". سامانه مدیریت نشریات علمی, 13, 2, 1401, 343-351. doi: 10.30476/mejc.2021.87375.1414
Akbari, Narjes, Safdari, Reza, Mansourian, Arash, Ehtesham, Hamideh. (1401). 'Development of a National Consensus Minimum Data Set for the Diagnosis and Treatment of Oral Cancer: Towards Precision Management', سامانه مدیریت نشریات علمی, 13(2), pp. 343-351. doi: 10.30476/mejc.2021.87375.1414
Akbari, Narjes, Safdari, Reza, Mansourian, Arash, Ehtesham, Hamideh. Development of a National Consensus Minimum Data Set for the Diagnosis and Treatment of Oral Cancer: Towards Precision Management. سامانه مدیریت نشریات علمی, 1401; 13(2): 343-351. doi: 10.30476/mejc.2021.87375.1414

Development of a National Consensus Minimum Data Set for the Diagnosis and Treatment of Oral Cancer: Towards Precision Management

Middle East Journal of Cancer
مقاله 16، دوره 13، شماره 2 - شماره پیاپی 50، تیر 2022، صفحه 343-351    اصل مقاله (127.27 K)
نوع مقاله: Original Article(s)
شناسه دیجیتال (DOI): 10.30476/mejc.2021.87375.1414
نویسندگان
Narjes Akbari1؛ Reza Safdari2؛ Arash Mansourian3؛ Hamideh Ehtesham* 4
1Department of Oral Medicine, School of Dentistry, Birjand University of Medical Sciences, Birjand, Iran
2Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
3Department of Oral Medicine and Dental Research Center, Faculty of Dentistry, Tehran University of Medical Sciences, Tehran, Iran
4Department of Health Information technology, Ferdows School of Paramedical and Health, Birjand University of Medical Sciences, Birjand, Iran
چکیده
Background: Due to the complexity of prognosis, diagnosis, and treatment in the process of providing care for patients with oral cancer, a large amount of data elements have been processed. The present study was conducted to provide a minimum data set for managing the data generated in the diagnosis and treatment processes of oral cancer by reviewing the specialized literature, medical records and by gathering expert opinions.
Method: This research was a descriptive cross-sectional study with the following steps: reviewing texts and records, developing a draft of data elements, organizing a panel of experts, Delphi techniques, and creating a final pattern.
Results: The framework proposed in this study for managing the data generated in the diagnosis and treatment processes of oral cancer was divided into six sections: management data with four-axis, historical data with four-axis, paraclinical indicators with two-axis, clinical indicators, data related to the therapeutic measures, and mortality data.
Conclusion: The systematic collection of the data associated with the diagnosis and treatment of the patients with oral cancer could provide a good basis for identifying patients or those who are susceptible to this type of cancer in the community. These data can also be used in programs to prevent the development and/or emergence of the disease, thus the health of the community.
کلیدواژه‌ها
Mouth neoplasms؛ Diagnosis؛ Therapeutics؛ Common data elements
اصل مقاله

How to cite this article:

Akbari N, Safdari R, Mansourian A, Ehtesham H. Development of a national consensus minimum data set for the diagnosis and treatment of oral cancer: towards precision management. Middle East J Cancer. 2022;13(2):343-51. doi: 10. 30476/mejc.2021.87375.1414.

مراجع
  1. Asmarian NS, Ruzitalab A, Amir K, Masoud S, Mahaki B. Area-to-Area Poisson Kriging analysis of mapping of county-level esophageal cancer incidence rates in Iran. Asian Pac J Cancer Prev. 2013;14(1):11-3. doi:10.7314/apjcp.2013.14.1.11.
  2. Kumar V, Abbas A, Aster J. Robbins and cotran pathologic basis of disease. 9th ed. Netherlands: Elsevier; 2014.
  3. Krishna Rao SV, Mejia G, Roberts-Thomson K, Logan R. Epidemiology of oral cancer in Asia in the past decade--an update (2000-2012). Asian Pac J Cancer Prev. 2013;14(10):5567-77. doi: 10.7314/apjcp.2013.14.10.5567.
  4. Chen XJ, Zhang XQ, Liu Q, Zhang J, Zhou G. Nanotechnology: a promising method for oral cancer detection and diagnosis. J Nanobiotechnology. 2018;16(1):52. doi: 10.1186/s12951-018-0378-6.
  5. Ehtesham H, Safdari R, Mansourian A, Tahmasebian S, Mohammadzadeh N, Pourshahidi S. Developing a new intelligent system for the diagnosis of oral medicine with case-based reasoning approach. Oral Dis. 2019;25(6):1555-63. doi:10.1111/odi.13108.
  6. Jeyaraj PR, Samuel Nadar ER. Computer-assisted medical image classification for early diagnosis of oral cancer employing deep learning algorithm. J Cancer Res Clin Oncol. 2019;145(4):829-37. doi:10.1007/s00432-018-02834-7.
  7. Davey CJ, Slade SV, Shickle D. A proposed minimum data set for international primary care optometry: a modified Delphi study. Ophthalmic Physiol Opt. 2017;37(4):428-39. doi: 10.1111/opo.12372.
  8. Zahmatkeshan M, Farjam M, Mohammadzadeh N, Noori T, Karbasi Z, Mahmoudvand Z, et al. Design of infertility monitoring system: Minimum data set approach. J Med Life. 2019;12(1):56. doi: 10.25122/jml-2018-0071.
  9. Ahmadi M, Alipour J, Mohammadi A, Khorami F. Development a minimum data set of the information management system for burns. Burns. 2015;41(5):1092-9. doi: 10.1016/j.burns.2014.12.009.
  10. Hornby K, Shemie SD, Appleby A, Dodd N, Gill J, Kim J, et al. Development of a national minimum data set to monitor deceased organ donation performance in Canada. Can J Anaesth. 2019;66(4):422-31. doi: 10.1007/s12630-018-01290-8.
  11. Sheykhotayefeh M, Safdari R, Ghazisaeedi M, Khademi SH, Seyed Farajolah SS, Maserat E, et al. Development of a minimum data set (MDS) for Csection anesthesia information management system (AIMS). Anesth Pain Med. 2017;7(2):e44132. doi:
    5812/aapm.44132.
  12. Stone E, Rankin N, Phillips J, Fong K, Currow DC, Miller A, et al. Consensus minimum data set for lung cancer multidisciplinary teams: Results of a Delphi process. Respirology. 2018;23(10):927-34. doi:10.1111/resp.13307.
  13. Schaller M, Hackl WO, Ianosi B, Ammenwerth E. Towards a systematic construction of a minimum data set for delirium to support secondary use of clinical routine data. Stud Health Technol Inform. 2019;264: 1026-30. doi: 10.3233/SHTI190380.
  14. Safdari R, Ghazi Saeedi M, Masoumi-Asl H, Rezaei-Hachesu P, Mirnia K, Mohammadzadeh N, et al. National minimum data set for antimicrobial resistance
    management: Toward global surveillance system. Iran J Med Sci. 2018;43(5):494-505.
  15. Damanabi S, Abdolnejad S, Karimi G. Suggested minimum data Set for speech therapy centers affiliated to Tabriz University of Medical Sciences. Acta Informatica Medica. 2015;23(4):243. doi: 10.5455/aim.2015.23.243-247.
  16. Kalankesh LR, Dastgiri S, Rafeey M, Rasouli N, Vahedi L. Minimum data set for cystic fibrosis registry: a case study in Iran. Acta Informatica Medica. 2015; 23(1):18. doi: 10.5455/aim.2015.23.18-21.
  17. Hajesmaeel-Gohari S, Bahaadinbeigy K, Tajoddini S, R Niakan Kalhori S. Minimum data set development for a drug poisoning registry system. Digit Health. 2019;5:2055207619897155. doi: 10.1177/2055207619897155.
  18. Jafar AJN, Sergeant JC, Lecky F. What is the interrater agreement of injury classification using the WHO minimum data set for emergency medical teams? Emerg Med J. 2020;37(2):58-64. doi: 10.1136/emermed-2019-209012.
  19. Sanson G, Alvaro R, Cocchieri A, Vellone E, Welton J, Maurici M, et al. Nursing diagnoses, interventions, and activities as described by a nursing minimum data set: a prospective study in an oncology hospital setting. Cancer Nurs. 2019;42(2):E39-E47. doi: 10.1097/NCC.0000000000000581.
  20. Hoben M, Poss JW, Norton PG, Estabrooks CA. Oral/dental items in the resident assessment instrument–minimum data set 2.0 lack validity: results of a retrospective, longitudinal validation study. Popul Health Metr. 2016;14(1):36. doi: 10.1186/s12963-016-0108-y.
  21. Sahu A, Krishna CM. Optical diagnostics in oral cancer: an update on Raman spectroscopic applications. J Cancer Res Ther. 2017;13(6):908. doi: 10.4103/0973-1482.191032.
  22. Deng H, Sambrook P, Logan R. The treatment of oral cancer: an overview for dental professionals. Aust Dent J. 2011;56(3):244-52. doi: 10.1111/j.1834-7819.2011.01349.x.
  23. Chiou SJ, Lin W, Hsieh CJ. Assessment of duration until initial treatment and its determining factors among newly diagnosed oral cancer patients: A populationbased retrospective cohort study. Medicine. 2016;95(50). doi: 10.1097/MD.0000000000005632.
  24. Shenoi R, Devrukhkar V, Sharma B, Sapre S, Chikhale A. Demographic and clinical profile of oral squamous cell carcinoma patients: A retrospective study. Indian J Cancer. 2012;49(1):21. doi: 10.4103/0019-509X.98910.
  25. Chuang SL, Su WWY, Chen SLS, Yen AMF, Wang CP, Fann JCY, et al. Population-based screening program for reducing oral cancer mortality in 2,334,299 Taiwanese cigarette smokers and/or betel quid chewers. Cancer. 2017;123(9):1597-609. doi:10.1002/cncr.30517.
  26. Inglehart R, Taberna M, Pickard R, Hoff M, Fakhry C, Ozer E, et al. HPV knowledge gaps and information seeking by oral cancer patients. Oral Oncol. 2016; 63:23-9. doi: 10.1016/j.oraloncology.2016.10.021.
  27. Macià F, Pumarega J, Gallén M, Porta M. Time from (clinical or certainty) diagnosis to treatment onset in cancer patients: the choice of diagnostic date strongly influences differences in therapeutic delay by tumor site and stage. J Clin Epidemiol. 2013;66(8):928-39.doi: 10.1016/j.jclinepi.2012.12.018.
  28. Macleod U, Mitchell E, Burgess C, Macdonald S, Ramirez A. Risk factors for delayed presentation and referral of symptomatic cancer: evidence for common cancers. Br J Cancer. 2009;101(S2):S92. doi: 10.1038/sj.bjc.6605398.
  29. Pérez MGS, Bagán JV, Jiménez Y, Margaix M, Marzal C. Utility of imaging techniques in the diagnosis of oral cancer. J Craniomaxillofac Surg. 2015;43(9):1880-94. doi: 10.1016/j.jcms.2015.07.037.
  30. Varela-Centelles P, López-Cedrún JL, Fernández-Sanromán J, Seoane-Romero JM, Santos de Melo N, Álvarez-Nóvoa P, et al. Key points and time intervals for early diagnosis in symptomatic oral cancer: a systematic review. Int J Oral Maxillofac Surg. 2017;46(1):1-10. doi: 10.1016/j.ijom.2016.09.017.
  31. Glick M. Burket's Oral Medicine. 12th ed: PMPHUSA, Ltd: USA; 2015.
  32. Mortazavi H, Safi Y, Baharvand M, Rahmani S, Jafari S. Peripheral exophytic oral lesions: A clinical decision tree. Int J Dent. 2017;2017:9193831. doi: 10.1155/2017/9193831.
  33. Sundermann BV, Uhlmann L, Hoffmann J, Freier K, Thiele OC. The localization and risk factors of squamous cell carcinoma in the oral cavity: a retrospective study of 1501 cases. J Craniomaxillofac Surg. 2018;46(2):177-82. doi: 10.1016/j.jcms.2017.10.019.
  34. Gupta P, Migliacci JC, Montero PH, Zanoni DK, Shah JP, Patel SG, et al. Do we need a different staging system for tongue and gingivobuccal complex squamous cell cancers? Oral Oncol. 2018;78:64-71.doi: 10.1016/j.oraloncology.2018.01.013.
  35. Han S, Chen Y, Ge X, Zhang M, Wang J, Zhao Q, et al. Epidemiology and cost analysis for patients with oral cancer in a university hospital in China. BMC Public Health. 2010;10(1):196. doi: 10.1186/1471-2458-10-196.
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