Association between <i>PIK3CA</i> activating mutations and outcomes in early-stage invasive lobular breast carcinoma treated with adjuvant systemic therapy
Bibliographic record
Abstract
BACKGROUND: activating mutations and efficacy of adjuvant endocrine therapy (ET) in patients with operable invasive lobular carcinoma (ILC). PATIENTS AND METHODS: A single institution study of patients with early-stage ILC treated between 2003 and 2008 was performed. Clinicopathological parameters, systemic therapy exposure and outcomes (distant metastasis-free survival [DMFS] and overall survival [OS]) were collected based on presence or absence of PIK3CA activating mutation in the primary tumor determined using a quantitative polymerase chain reaction (PCR)-based assay. An association between PIK3CA mutation status and prognosis in all patient cohort was analyzed by Kaplan-Meier survival analysis, whereas an association between PIK3CA mutation and ET was analyzed in estrogen receptors (ER) and/or progesterone receptors (PR)-positive group of our patients by the Cox proportional hazards model. RESULTS: Median age at diagnosis of all patients was 62.8 years and median follow-up time was 10.8 years. Among 365 patients, PIK3CA activating mutations were identified in 45%. PIK3CA activating mutations were not associated with differential DMFS and OS (p = 0.36 and p = 0.42, respectively). In patients with PIK3CA mutation each year of tamoxifen (TAM) or aromatase inhibitor (AI) decreased the risk of death by 27% and 21% in comparison to no ET, respectively. The type and duration of ET did not have significant impact on DMFS, however longer duration of ET had a favourable impact on OS. CONCLUSIONS: PIK3CA activating mutations are not associated with an impact on DMFS and OS in early-stage ILC. Patients with PIK3CA mutation had a statistically significantly decreased risk of death irrespective of whether they received TAM or an AI.
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 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) | 0.000 | 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 | 0.000 | 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".