Abstract P5-13-06: Seasonal variation in onset of inflammatory breast cancer: Evidence of an infectious trigger
Bibliographic record
Abstract
Abstract Introduction: Inflammatory breast cancer (IBC) is a rare but extraordinarily aggressive disease with a number of studies indicating that environmental factors play the most important role. We have identified four reported clusters of IBC and our investigations thus far suggest that local toxic or infectious agents could be involved in the pathogenesis of the disease. IBC, like Burkitt's lymphoma (BL) has been reported to cluster and both have been implicated with infectious agents. Since BL has been reported to have a seasonal variation attributed to acute malaria symptoms as the precipitating agent, we decided to investigate the seasonality of IBC in two populations. Methods: For our analysis we used the datasets of two IBC referral groups. The first group consisted of a series of 163 consecutive cases of patients seen at Fox Chase Cancer Center (FCCC) almost all being from the Northeast U.S. (NE) and Canada. At the time of initial visit a detailed series of questions was specifically directed at identifying the accurate time of the first onset of symptoms/signs including skin rash, swelling, pain, nipple retraction and palpable mass. The second was the IBC registry (IBCR), established at the George Washington University with the purpose of collecting standardized clinical and epidemiologic data (including a detailed interview) and biospecimens from patients with IBC in the U.S and Canada. Complete data on patients in both groups were evaluated, including diagnostic workup, pathologic findings and treatment. Results: Of the 163 FCCC patients, 156 had the month of onset of symptoms clearly delineated. Of the 161 patients in the IBCR, 153 had month of symptomatic onset defined. In the combined groups, 181 NE patients were compared with 63 from the South. A seasonal pattern was noted in the NE patients, a bimodal pattern showing most patients with onset in March and July-Sept. No seasonal pattern was noted in patients from the South. Conclusion: The reports of IBC clusters are consistent with an acute triggering factor, possibly an infection. The seasonality we observed in NE patients but not in southern patients is consistent with this hypothesis. We are currently continuing to investigate clusters of IBC and are testing for specific candidate infectious agents as well as candidate environmental toxic agents to further understand possible triggers for this disease. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P5-13-06.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".