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민병소,김남규,표주연,김호근,성진실,금기창,손승국,조창환 대한대장항문학회 2011 Annals of Coloproctolgy Vol.27 No.1
Background: We investigated the prognostic significance of tumor regression grade (TRG) after preoperative chemoradiation therapy (preop-CRT) for locally advanced rectal cancer especially in the patients without lymph node metastasis. Methods: One-hundred seventy-eight patients who had cT3/4 tumors were given 5,040 cGy preoperative radiation with 5-fluorouracil/leucovorin chemotherapy. A total mesorectal excision was performed 4-6 weeks after preop-CRT. TRG was defined as follows: grade 1 as no cancer cells remaining; grade 2 as cancer cells outgrown by fibrosis; grade 3 as a minimal presence or absence of regression. The prognostic significance of TRG in comparison with histopathologic staging was analyzed. Results: Seventeen patients (9.6%) showed TRG1. TRG was found to be significantly associated with cancer-specific survival (CSS; P = 0.001) and local recurrence (P = 0.039) in the univariate study, but not in the multivariate analysis. The ypN stage was the strongest prognostic factor in the multivariate analysis. Subgroup analysis revealed TRG to be an independent prognostic factor for the CSS of ypN0 patients (P = 0.031). TRG had a stronger impact on the CSS of ypN (-) patients (P = 0.002) than on that of ypN (+) patients (P = 0.521). In ypT2N0 and ypT3N0, CSS was better for TRG2 than for TRG3 (P = 0.041, P = 0.048), and in ypN (-) and TRG2 tumors, CSS was better for ypT1-2 than for ypT3-4 (P = 0.034). Conclusion: TRG was found to be the strongest prognostic factor in patients without lymph node metastasis (ypN0), and different survival was observed according to TRG among patients with a specific histopathologic stage. Thus, TRG may provide an accurate prediction of prognosis and may be used for f tailoring treatment for patients without lymph node metastasis.
閔丙昭 釜山工業大學校 1968 論文集 Vol.6 No.-
統計學上 最近30年間 發達한 推測統計學 또는 推計學(Stochastics)에서 一般的으로 統計量의 分布를 標本分布라 한다. 標本分布의 法則은 그 母集團의 分布法則으로부터 數學的으로 誘導되기 마련이다. 母集團의 分布法則으로서 가장 잘 쓰이는 것은 正規分布인데 이로부터 誘導되는 標本分布도 統計量의 種類에 따라서 여러 가지가 있다. 其中에도 基本的인 것은 正規分布 χ²-分布, Fisher의 Z-分布, Snedecor의 F-分布, “Student”의 t-分布等이다. 標本論에서는 우리가 찾는 統計資料는 모두 어떤 母集團으로 부터의 標本이라고 보는 것이다. 그리고 特히 이것은 任意標本이라고 볼 때, 먼저 母集團의 性質을 假定하여 놓고 標本으로부터 計算해낸 統計量의 값(實現値라함)과 그의 標本分布의 法則으로부터 주어진 統計資料가 果然 이 母集團으로 부터의 任意標本으로서 볼 수 있는지 이민지를 檢定 한다든가 또는 適當한 統計量을 選擇하여 現實의 標本으로부터 計算한 그의 實現値외 그 標本分布의 性質로부터 母集團의 未知母數를 推定하는 等이 標本論의 主題인 것이다.