Abstract 3422: The influence of genetic and clinical factors on the outcome following a diagnosis of small cell carcinoma of the ovary, hypercalcemic type
Bibliographic record
Abstract
Abstract Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is the most common undifferentiated ovarian tumor diagnosed in women below the age of 40. While it is uncommon, with only ∼500 cases reported, it is an extremely aggressive tumor, with long term survival rates of <30% in early stage disease. Recently, we discovered that SCCOHT is a monogenic disease, attributable to germline and somatic deleterious mutations in the chromatin remodeling gene, SMARCA4. Since then, single case reports have been published on women affected with SCCOHT, but no large studies have been conducted on the effect of these mutations, germline or somatic, on the disease. Furthermore, while numerous publications have described the therapies used in single cases or small cohorts of SCCOHT patients, treatment remains varied, with no standardized protocols. In an attempt to clarify which factors have an effect on the course of the disease, we reviewed all published and a cohort of unpublished SCCOHT cases and collected information on the following factors: stage at diagnosis, age at diagnosis, treatment modality used (chemotherapy/radiotherapy/high dose chemotherapy), mutation type (germline/somatic), and length of survival. We were able to acquire information in at least 2 of these parameters in 267 cases and performed multiple analyses. Clinically, we found that the greatest influence on patient outcome was related to stage at diagnosis (p < 0.001) and treatment modality (p = 0.01), while age at diagnosis had no significant effect (p = 0.72). Molecularly, the presence of a germline mutation in the patient did not affect the age of onset (p = 0.86), nor did it have an effect on the length of survival of the patient (p = 0.63). Overall, this is the largest study conducted to date analyzing the influence of clinical factors on the outcome of patients diagnosed with SCCOHT, and is the first large study to analyze the effect of germline mutations on the outcome of these patients. Citation Format: Leora Witkowski, Catherine Goudie, Pilar Ramos, Anthony N. Karnezis, Talia Boshari, Patricia Pautier, Michel Longy, James A. Knost, Emmanouil Saloustros, W Glenn McCluggage, Martin Hasselblatt, William P. Hendricks, David Huntsman, Douglas A. Levine, Jeffrey Trent, William D. Foulkes. The influence of genetic and clinical factors on the outcome following a diagnosis of small cell carcinoma of the ovary, hypercalcemic type. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3422.
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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 | 0.001 | 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".