Predicting outcome in papillary thyroid carcinoma: Development of a reliable prognostic scoring system in a cohort of 1779 patients surgically treated at one institution during 1940 through 1989

Ian D. Hay, Erik J. Bergstralh, John R. Goellner, Janet R. Ebersold, Clive S. Grant

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Abstract

Background. Multivariate analyses in papillary thyroid carcinoma (PTC) have shown that age, tumor size, local invasion and distant metastasis are independent predictive variables. This study attempted to define a reliable prognostic scoring system for predicting PTC mortality rates with 15 candidate variables that included completeness of primary tumor resection but excluded histologic grade and DNA ploidy. Methods. The study group comprised 1779 patients with PTC (followed up for > 26,000 patient-years), divided by treatment dates into 1940 to 1,964 (n = 764) and 1965 to 1989 (n = 1015). Cox model analysis and stepwise variable selection led to a prognostic model initially derived from the training set (n = 764). The initial prognostic score was thereafter validated externally with the later (1965 to 1989) "test" data set. Results. The final model included five variables abbreviated by metastasis, age, completeness of resection, invasion, and size (MACIS). The final prognostic score was defined as MACIS = 3.1 (if aged ≤ years) or 0.08 X age (if aged {succeeds above single-line equals sign}40 years), + 0.3 Xtumor size (in centimeters), +1 (if incompletely resected), +1 (if locally invasive), +3 (if distant metastases present). Twenty-year cause-specific survival rates for patients with MACIS less than 6, 6 to 6.99, 7 to 7.99, and 8+ were 99%, 89%, 56%, and 24%, respectively (p < 0.0001). Conclusions. Because the five variables needed for MACIS scoring are readily available after primary operation, such a prognostic system could have widespread applicability in assessment of PTC.

Original languageEnglish (US)
Pages (from-to)1050-1058
Number of pages9
JournalSurgery
Volume114
Issue number6
StatePublished - Dec 1993

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ASJC Scopus subject areas

  • Surgery

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