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- Jerevall, Piiha-Lotta, et al.
(author)
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Prognostic utility of HOXB13:IL17BR and Molecular Grade Index in early-stage breast cancer patients from the Stockholm trial
- 2011
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In: British Journal of Cancer. - : Nature Publishing Group. - 0007-0920 .- 1532-1827. ; 104:11, s. 1762-1769
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Journal article (peer-reviewed)abstract
- Background: A dichotomous index combining two gene expression assays, HOXB13:IL17BR (H:I) and molecular grade index (MGI), was developed to assess risk of recurrence in breast cancer patients. The study objective was to demonstrate the prognostic utility of the combined index in early-stage breast cancer. Methods: In a blinded retrospective analysis of 588 ER-positive tamoxifen-treated and untreated breast cancer patients from the randomized prospective Stockholm trial, H:I and MGI were measured using real-time RT-PCR. Association with patient outcome was evaluated by Kaplan-Meier analysis and Cox proportional hazard regression. A continuous risk index was developed using Cox modeling. Results: The dichotomous H:I+MGI was significantly associated with distant recurrence and breast cancer death. The >50% of tamoxifen-treated patients categorized as low-risk had <3% 10-year distant recurrence risk. A continuous risk model (Breast Cancer Index (BCI)) was developed with the tamoxifen-treated group and the prognostic performance tested in the untreated group was 53% of patients categorized as low-risk with an 8.3% 10-year distant recurrence risk. Conclusion: Retrospective analysis of this randomized, prospective trial cohort validated the prognostic utility of H:I+MGI and was used to develop and test a continuous risk model that enables prediction of distant recurrence risk at the patient level.
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- Stål, Olle, et al.
(author)
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Validation of Prognostic Utility of HOXB13:IL17BR and Molecular Grade Index in Early Stage Breast Cancer : in CANCER RESEARCH, vol 69, issue 24, pp 504S-504S
- 2009
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Conference paper (peer-reviewed)abstract
- Background. HOXB13:IL17BR (H:I) is a two gene expression index, which has been shown to be an independent prognostic factor in estrogen receptor (ER)-positive lymph node-negative (N0) breast cancer. A molecular grade index (MGI) measures the expression of five proliferation-related genes. An algorithm based on dichotomized H:I and MGI stratifying patients into three risk groups has been shown to be superior to either alone in predicting risk of distant metastasis in ER+/N0 patients. Further validation in larger cohorts is needed to establish its clinical performance. A continuous predictor combining H:I and MGI is desirable for making individualized risk assessment in the clinical setting. Methods. During 1976 through 1990 the Stockholm Breast Cancer Group conducted a randomized clinical trial comparing adjuvant tamoxifen with control in 1780 postmenopausal women considered to be at low risk of recurrence (N0 and tumor size < 3 cm). We measured H:I and MGI using a real time PCR assay in 769 patients from this trial based on sample availability. Correlation of gene expression indices with distant metastasis and death due to breast cancer was evaluated by Kaplan-Meier analysis and Cox proportional hazard regression. Modeling was also used to develop a continuous risk index as a function of both H:I and MGI. Results. Using pre-specified cutoff points and combination algorithm, H:I, MGI and their combination each was significantly associated with both distant metastasis-free survival and breast cancer-specific survival (Table 1). Furthermore, we used the ER+ tamoxifen-treated subset (n=314) to develop a continuous risk model (Breast Cancer Index or BCI) combining both H:I and MGI. The prognostic utility of BCI was then successfully validated in the untreated subset in this trial and three additional previously published cohorts. BCI consistently identified ∼50% patients with a very low 10-year recurrence risk (< 5%). Discussion. This large retrospective analysis of a randomized clinical trial cohort validated the prognostic utility of H:I, MGI, and their combination. With the continuous risk model, this RT-PCR-based assay allows prediction of risk of recurrence at the individual level, which may help tailor personalized treatment strategy.
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