Liaquat Medical Research Journal (Dec 2021)

Validation of onco-assist survival prediction tool in stage I, II and IIIcolon cancer among Asian patients

  • Fayaz Hussain Mangi,
  • Jawaid Naeem Qureshi

DOI
https://doi.org/10.38106/LMRJ.2021.3.04-05
Journal volume & issue
Vol. 3, no. 4
pp. 107 – 111

Abstract

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Clinical calculators and predictors are now commonly used in clinical practice to predict most accurate clinical outcome and provide guidance for appropriate therapy. One of the most used calculator is Onco-assist. This study was conducted to compare onco-assist prediction of the patients diagnosed with colon cancer Stage I, II and III. Data was retrospectively collected from 88 patients of colon cancer diagnosed over the period of 11 years (2008 to 2018) and registered at Nuclear Institute of medicine and radiotherapy (NIMRA), Hospital, Jamshoro Sindh. These patients received primary surgical therapy without any neo-adjuvant systemic chemotherapy. Survival assessed on onco-assist prediction algorithm using the defined parameters and compared with the actual survival according to the grade of the tumour. The clinical calculator onco-assist incorporated seven variables: gender, age number of lymph nodes examined, number of tumor-involved lymph nodes, T = (1-4), grade (low / high), adjuvant chemo received (yes / no) if yes then only 5FU or 5FU plus Oxaliplatin based. Onco-assist predicted five-year survival rate in well differentiated tumours with and without chemotherapy as 84% and 80% respectively, in moderately differentiated tumour with and without chemotherapy as 78% and 76% respectively. For poorly differentiated tumours the predicted survival rate with and without chemotherapy was 73%. While actual achieved survival was 35%, 52% and 17% for well, moderately and poorly differentiated cancers. This clinical calculator onco-assist includes limited parameters and limited adjuvant therapy options thus the prediction of cancer survival following surgery in stage I –III colon cancer does not appear to accurately predict outcome in Asian population.

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