Risk-stratified Distant Metastatic Thyroid Cancer with Clinicopathological Factors and BRAF/TERT Promoter Mutations.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 3/4)
유사 논문P · Population 대상 환자/모집단
1055 patients without DM (Non-DM-TCs) were retrospectively reviewed.
I · Intervention 중재 / 시술
thyroidectomy at Jiangyuan Hospital Affiliated to Jiangsu Institute of Nuclear Medicine from January 2008 to December 2021
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSIONS] This study proposes a TLBT risk classifier consisting of T3/T4 stages, LNM (n>5), and mutations for predicting DM-TCs. TLBT risk stratification may help clinicians make personalized treatment management and follow-up strategies.
[OBJECTIVE] To assess the prognostic value of clinicopathological factors as well as and promoter mutations in predicting distant metastasis in patients with papillary thyroid cancer.
- 표본수 (n) 896
APA
Cheng X, Zhou Y, et al. (2023). Risk-stratified Distant Metastatic Thyroid Cancer with Clinicopathological Factors and BRAF/TERT Promoter Mutations.. Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association, 131(11), 577-582. https://doi.org/10.1055/a-2177-1051
MLA
Cheng X, et al.. "Risk-stratified Distant Metastatic Thyroid Cancer with Clinicopathological Factors and BRAF/TERT Promoter Mutations.." Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association, vol. 131, no. 11, 2023, pp. 577-582.
PMID
37922948 ↗
Abstract 한글 요약
[OBJECTIVE] To assess the prognostic value of clinicopathological factors as well as and promoter mutations in predicting distant metastasis in patients with papillary thyroid cancer.
[DESIGN] The status of and mutations were available in 1,208 thyroid cancer patients who received thyroidectomy at Jiangyuan Hospital Affiliated to Jiangsu Institute of Nuclear Medicine from January 2008 to December 2021. Based on inclusion criteria, 99 distant metastasis thyroid cancers (DM-TCs) and 1055 patients without DM (Non-DM-TCs) were retrospectively reviewed.
[RESULTS] After univariate and multivariate analyses, a risk model was established for DM prediction based on factors: T3/T4 stage, lymph node metastasis (LNM) number over 5, and mutations (TLBT). It was defined based on the number of TLBT factors: low risk (no risk factor, n=896), intermediate risk (1 risk factor, n=199), and high risk (≥2 risk factors, n=59). Notably, compared with patients with low and intermediate risks, patients assigned to high TLBT risk have a shorter time of DM disease-free survival. Except for gene mutation, other factors were also included in the 2015 American Thyroid Association (ATA) risk guideline. Comparing with the ATA risk category, this risk model showed a better performance in predicting DM-TCs.
[CONCLUSIONS] This study proposes a TLBT risk classifier consisting of T3/T4 stages, LNM (n>5), and mutations for predicting DM-TCs. TLBT risk stratification may help clinicians make personalized treatment management and follow-up strategies.
[DESIGN] The status of and mutations were available in 1,208 thyroid cancer patients who received thyroidectomy at Jiangyuan Hospital Affiliated to Jiangsu Institute of Nuclear Medicine from January 2008 to December 2021. Based on inclusion criteria, 99 distant metastasis thyroid cancers (DM-TCs) and 1055 patients without DM (Non-DM-TCs) were retrospectively reviewed.
[RESULTS] After univariate and multivariate analyses, a risk model was established for DM prediction based on factors: T3/T4 stage, lymph node metastasis (LNM) number over 5, and mutations (TLBT). It was defined based on the number of TLBT factors: low risk (no risk factor, n=896), intermediate risk (1 risk factor, n=199), and high risk (≥2 risk factors, n=59). Notably, compared with patients with low and intermediate risks, patients assigned to high TLBT risk have a shorter time of DM disease-free survival. Except for gene mutation, other factors were also included in the 2015 American Thyroid Association (ATA) risk guideline. Comparing with the ATA risk category, this risk model showed a better performance in predicting DM-TCs.
[CONCLUSIONS] This study proposes a TLBT risk classifier consisting of T3/T4 stages, LNM (n>5), and mutations for predicting DM-TCs. TLBT risk stratification may help clinicians make personalized treatment management and follow-up strategies.
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