【佳學(xué)基因檢測】開發(fā)用于篩選 BRCA1/2 突變的評分系統(tǒng)

腫瘤基因檢測公司排名國內(nèi)熱點(diǎn)

與同行交流時(shí)知悉《Methods Mol Biol》在?2010;653:237-47發(fā)表了一篇題目為《開發(fā)用于篩選 BRCA1/2 突變的評分系統(tǒng)》腫瘤靶向藥物治療基因檢測臨床研究文章。該研究由Gareth R Evans,?Fiona Lalloo等完成。促進(jìn)了腫瘤的正確治療與個(gè)性化用藥的發(fā)展，進(jìn)一步強(qiáng)調(diào)了基因信息檢測與分析的重要性。

腫瘤靶向藥物及正確治療臨床研究內(nèi)容關(guān)鍵詞：

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腫瘤靶向治療基因檢測臨床應(yīng)用結(jié)果

BRCA1 和 BRCA2 致病性突變的基因檢測選擇是醫(yī)療保健的一個(gè)重要領(lǐng)域。雖然突變分析的測試成本正在下降，但北美的測試成本仍然超過 3,000 美元。大多數(shù)國家規(guī)定，在進(jìn)行突變分析之前，應(yīng)該有至少 10-20% 的可能性在一個(gè)家庭中檢測到 BRCA1 或 BRCA2 突變。已經(jīng)開發(fā)了許多基于計(jì)算機(jī)的模型來評估這種可能性，并且這些模型繼續(xù)得到改進(jìn)，以結(jié)合突變頻率、乳腺癌發(fā)病率和腫瘤組織學(xué)。然而，這些在繁忙的診所中可能很耗時(shí)且難以使用。曼徹斯特評分系統(tǒng)于 2003 年開發(fā)，我們繼續(xù)驗(yàn)證其在西方人群中的使用。評分系統(tǒng)在 10% 和 20% 的測試閾值下都可以很好地區(qū)分，并且可以與更復(fù)雜的基于計(jì)算機(jī)的模型進(jìn)行很好的比較。然而，它不應(yīng)該以目前的形式用于創(chuàng)始人人群或乳腺癌發(fā)病率低的人群，盡管可以使用較低的點(diǎn)閾值來確定適當(dāng)?shù)慕刂怪?。本章將介紹曼徹斯特分?jǐn)?shù)的發(fā)展及其與其他模型的比較。

腫瘤發(fā)生與反復(fù)轉(zhuǎn)移國際數(shù)據(jù)庫描述：

Selection for genetic testing for pathogenic mutations in BRCA1 and BRCA2 is an important area of healthcare. While testing costs for mutational analysis are falling, costs of tests in North America remain in excess of $3,000. Most countries state that there should be at least a 10-20% likelihood of detecting a mutation in BRCA1 or BRCA2 within a family before mutational analysis is performed. A number of computer-based models have been developed to assess this likelihood, and these continue to be improved to incorporate mutation frequencies, breast cancer incidence and tumour histology. However, these can be time-consuming and difficult to use in a busy clinic. The Manchester scoring system was developed in 2003, and we have continued to validate its use in Western populations. The scoring system discriminates well at both the 10 and 20% threshold for testing and compares very well with more complex computer-based models. However, it should not be used in its current form in founder populations or populations with low incidence of breast cancer, although a lower points threshold could be used to determine an appropriate cut off. The development of the Manchester score and its comparison with other models will be described in this chapter.