Successful Use of Erlotinib in Treating Recurrent Thymic Carcinoma: A Case Report
Bibliographic record
Abstract
Thymic carcinomas are rare and aggressive tumors. Primary treatment for these tumors consists of surgical resection, followed by adjuvant radiation therapy or platinum based chemotherapy. Unfortunately these tumors often exhibit a high incidence of local recurrence and metastasis despite treatment. Of recent interest are new targeted therapies such as Tarceva® (erlotinib), an epidermal growth factor receptor (EGFR) inhibitor, for treatment of recurrent thymic carcinoma. Unfortunately recent literature has shown little success with its use, except for a few isolated case reports. Here we present a unique case of progressive disease despite 4 cycles of cisplatin, doxorubicin, vincristine, and cyclophosphamide (ADOC) therapy, and subsequent treatment with 150mg erlotinib daily resulting in partial response at 6 months with tumor shrinking in size and resolution of many metastatic nodules. World J Oncol. 2013;4(4-5):214-216 doi: http://dx.doi.org/10.4021/wjon707w
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".