Elevated Tumor Markers in the Different Breast Cancer Subtypes; Percentage and Correlation with Outcome.
Bibliographic record
Abstract
Abstract Background: Tumor markers (TMs) are widely used in breast cancer to monitor patients with metastatic disease during active treatment in conjunction with diagnostic imaging, history and physical examination. Studies of CA15-3 and CEA in metastatic disease have yielded positivity rates of approximately 80% and 40%, respectively. There is less information regarding CA-125 and breast carcinoma. Recently, there has been a renewed interest in tumor markers and their potential as therapeutic targets, including vaccine development, in various cancers. Early studies have reported an association between CA 15-3 levels and ER positivity. As far as we are aware, this is the first study to report elevated TM levels in the different breast subtypes and their correlation with outcome in each subtype. Aim: To document the rate of elevated tumor markers (CEA, CA15-3, CA-125) in the different subtypes and correlate TM with outcome. Methods: Women with breast cancer diagnosed between 1986 and 1992 and referred to the British Columbia Cancer Agency with M1 disease at presentation or who later developed a distant relapse were included. Archival paraffin tissue blocks were used to construct a tissue microarray. Breast cancer subtypes were defined as Luminal A (ER/PR+, HER2- and Ki67 <14%), Luminal B (ER/PR+ and HER2- and Ki67 ≥14%), Luminal HER2 (HER2+ and ER/PR+), HER2 (HER2+ and ER-and PR-), and Basal {HER2-, ER-PR- and (CK 5/6+ and/or EGFR+)} using immunohistochemical staining. In addition, we examined the triple negative (ER-, PR-, HER2-) non-basal subgroup. Levels of TM values (CA-15-3, CEA, CA-125) within 3 months of distant relapse date or anytime after were captured and percentage of elevated values (CA15-3>28, CEA>4, CA-125> 35) among the different subtypes were reported. Kaplan Meier (KM) plots were created for cases with elevated TM versus non-elevated TM cases. Results: 1,656 cases with distant metastases were potentially eligible for inclusion. Excluded cases: 428 cases without any linkage to TM data, 16 cases with subsequent contaralateral breast cancer (CBC) and no TM between the time of distant relapse and CBC, 127 cases with TM >3 months before distant relapse, and 187 cases where breast cancer subtype could not be determined. The percentage of TMs among the different breast cancer subtypes is shown in the table. Median duration of survival from time of diagnosis with metastatic disease was significantly shorter for patients with elevated TMs vs. those with normal TM values, p=0.003. Similar results were found when stratifying the results by subtype, with only Lum A and B attaining statistical significance, p=0.002 and p=0.016 respectively.Conclusion: Elevated TMs are documented in all breast cancer subtypes, with a significantly higher percentage of elevated TMs in luminal versus non-luminal groups. The lowest frequency of elevated TMs was documented in the non-basal TN cases. Elevated TMs in the metastatic setting predict worse outcome for Lum A/B subtypes.Table 1 : Percentage of elevated TMs among the different breast cancer subtypesSubtypeany TM %CA 15-3 %CEA %CA-125 %Lum A87816448Lum B88836054Lum Her2+86766339Her2+,ER-78705443Basal70642764Non Basal, Triple negative61582540p value<0.0010.001<0.0010.71 Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2125.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".