Breast Cancer Symposium: Women with Low-Risk Breast Cancer Derive Little Benefit from Paclitaxel; Tissue Microarray Approach Validated in Clinical Trial Samples
Bibliographic record
Abstract
SAN FRANCISCO—Researchers previously found that women with HER2-negative, estrogen-receptor positive, node-positive breast cancer gained little additional benefit when paclitaxel was added to adjuvant chemotherapy with doxorubicin plus cyclophosphamide (AC). Now investigators confirm that conclusion with a larger sample size and the relatively new technology of tissue microarrays, according to data presented here at the Breast Cancer Symposium. The investigators also propose a new standard for Level 1 evidence, which they say would move scientific discoveries into clinical practice much more quickly. ‘Very Important Study’ “This is a very important study,” said Lori J. Pierce, MD, Professor of Radiation Oncology at the University of Michigan Health System, who was not involved in the study but chaired the program committee for the meeting. “The methods used will help clinicians select those breast cancers that will respond to specific chemotherapies, and spare patients whose cancers will not respond to specific agents. Studies such as this will really help us to accomplish some very important goals.”LORI J. PIERCE, MD: “The methods used in this study will help clinicians select those breast cancers that will respond to specific chemotherapies, and spare patients whose cancers will not respond to specific agents. Studies such as this will really help us to accomplish some very important goals.”In the previously published study, Daniel Hayes, MD, of the University of Michigan and colleagues tested the HER2 expression in tumors from 1,322 of the 3,121 women who participated in a Cancer and Leukemia Group B (CALGB) trial that compared adjuvant AC therapy alone or followed by paclitaxel. Dr. Hayes used the HER2 data and chart-reported ER status to show that women whose tumors were HER2-negative and ER-positive derived little or no benefit from the addition of paclitaxel. In the current study, a team led by Torsten Nielsen, MD, PhD, Associate Professor of Pathology at the University of British Columbia in Vancouver and a member of the CALGB correlative science committee, used tissue microarrays to test expression of five biomarkers in tumor samples from 2,039 of the women in that trial. Unlike traditional immunohistochemistry which treats each patient sample individually, using tissue microarrays researchers can put 200 specimens on a single slide and probe them using immunohistochemistry, fluorescence in situ hybridization, or RNA in situ hybridization. With that tool available, Dr. Nielsen and colleagues tested the tumor samples for expression of five proteins, including ER, HER2, Ki67, epidermal growth factor receptor (EGFR), and the basal marker cytokeratin 5/6 (ck5). Based on pre-established cut points, 19% of the tumors were HER2-positive, 60% were ER-positive, 30% were Ki67-positive, 36% ck5-positive, and 27% EGFR-positive. The tissue microarrays appeared to be comparable to other detection methods, showing a 93% concordance for HER2 and an 87% concordance for ER status in previously tested samples.TORSTEN O. NIELSEN, MD, PhD: “The most important aspect of these studies is the predictive capacity of these scores for response to paclitaxel. The tissue microarray approach gives results similar to what would be obtained with more expensive, slower tests of whole sections.”“We felt that was pretty good, considering that we were comparing it with community hospital assays that had been done with different methodologies and different cut points,” Dr. Nielsen said. “These numbers are comparable to the agreement levels between two pathologists looking at the same material” Together the five markers can be used to assign tumors into the five intrinsic subtypes of breast cancer, which were originally defined using gene expression arrays. Forty-one percent of the women had luminal A tumors (ER positive, HER2 negative, Ki67 low); 18% luminal B (ER positive, HER2 positive or Ki67 high); 11% HER2 enriched (ER negative, HER2 positive); 23% basal (ER negative, HER2 negative, ck5 or EGFR positive); and 6% could not be assigned. Results When Dr. Nielsen's team examined the impact of paclitaxel on disease-free survival in each of these subgroups of patients, their results resembled the previously published data. Women with luminal A tumors did not show any benefit from the addition of paclitaxel, while women with luminal B tumors had a 31% reduction in risk, which was statistically significant. Women with HER2-enriched tumors also benefited, with a 43% reduction in risk, as did the women with core basal tumors, with a 25% reduction in risk of recurrence. “The most important aspect of these studies is the predictive capacity of these scores for response to paclitaxel,” Dr. Nielsen said. “The tissue microarray approach gives results similar to what would be obtained with more expensive, slower tests of whole sections.” First Times in Large Trial Dataset, Requires Only Small Amount of Tissue In an interview, Dr. Nielsen noted that this is the first time tissue microarrays have been used on a large clinical trial dataset. Furthermore, the approach is compatible with formalin-fixed, paraffin-embedded samples and requires only a small amount of tissue (0.6 mm cores). Thus the technique is likely to be useful in reanalyzing data gathered from previously completed randomized trials and will open up new avenues of research. New Type Level 1 Evidence With that in mind, Dr. Nielsen and others are promoting a new type of level I evidence that would be sufficient to change practice guidelines. Now, only data from prospective randomized clinical trials or meta-analyses are considered Level I evidence. Retrospective analyses of previously completed clinical trial data, such as the current study, are considered Level 2 evidence and are not adequate to change practice guidelines. ‘Retrospective Prospective Studies’ The scientists would like to see that status quo changed. Dr. Nielsen and others have coined the phrase “retrospective prospective studies” to describe studies that use prospectively designed methods to test hypotheses using samples from already completed clinical trials. As in the study he presented, these studies would require that all of the methods be carefully laid out ahead of time, including cut points for biomarkers. The scientists propose that two retrospective prospective trials should be considered Level I evidence, and sufficient to change practice. Dr. Hayes and others published a commentary on this idea in the November 4 issue of the Journal of the National Cancer Institute. This approach would allow investigators to examine the value of a predictive biomarker, for example, without having to wait the 10 or so years it takes to complete a randomized clinical trial. “Women who volunteered for these trials 10 or 15 years ago are still able to contribute new information with new molecular studies that will help their daughters' generation make better choices about what to do with breast cancer,” Dr. Nielsen said. Is his newly reported data sufficient to change practice now? Dr. Nielsen says it is one p iece in a growing body of evidence suggesting that a woman whose tumor has a good molecular profile may not need to be treated as aggressively as she might otherwise be: “It is one piece of evidence that an oncologist and patient are going to be balancing when they are making that decision. It is not at the level yet that you would put down an official practice guideline that says that women who have a low Ki67 index, who are ER-positive, and HER2-negative should not be given paclitaxel.” For that, researchers need to corroborate it with one more retrospective prospective study performed “as rigorously as this one,” Dr. Nielsen said, adding that he is looking for a second, already-completed randomized trial data set for that study now. www.oncology-times.com Meeting Cosponsors The Breast Cancer Symposium is cosponsored by the American Society of Clinical Oncology, the American Society of Breast Disease, American Society of Breast Surgeons, American Society for Radiation Oncology, National Consortium of Breast Centers, and Society of Surgical Oncology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".