Carcinosarcoma: A single centre experience and population based study.
Bibliographic record
Abstract
e22526 Background: Carcinosarcomas, consisting of biphasic morphological patterns including both epithelial and sarcomatoid components, are rare malignant tumours. We highlight the incidence and outcomes of this unique disease at our large cancer referral centre. Methods: A retrospective review consisting of carcinosarcoma patients over a 10 years span from 1/1/2005 to 1/1/2015 with follow up data through to 2/2017 to ensure at least 2 years of post-treatment data collection by purveying Electronic Medical Records, paper charts and where required, communication with peripheral facilities, was conducted. Inclusion and exclusion criteria were histologic confirmation and age < 18 years respectively. A comprehensive literature review was also conducted to identify current outcomes trends. Results: Seventy patients meeting selection criteria were identified out of a total of 968 entries involving all soft tissue tumors. Incidence was mainly of gynecological origin (88.5%), in female patients (92.9%) and chiefly Grade 3 disease. Commonest presenting symptom was vaginal bleeding (54.3%). A majority received surgery (90.0%) primarily with a curative intent. 54.3% of the patients received chemotherapy and 51.4% received radiation; both largely in an adjuvant setting. Commonest treatment regimen was Carboplatin/Paclitaxel (73.7%) with a median of 6 cycles provided. Overall, 11 patients had a component of local failure with the latest failure recorded at 13.3 months. Conclusions: Treatment outcomes for carcinosarcoma over the years remain comparable to published results although there remains room for improvement. More research is required to identify strategies for improvement in both locoregional and systemic control. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".