Use of tamoxifen in the treatment of malignant melanoma
Bibliographic record
Abstract
BACKGROUND: Tamoxifen has been used in the treatment of patients with metastatic malignant melanoma either as a single agent or, more commonly, in combination with other chemotherapeutic agents. The aim of the current study was to summarize the available clinical evidence on the role of the tamoxifen in different combination chemotherapy regimens because clinical studies including tamoxifen have produced inconclusive results. METHODS: The authors designed a systematic review and metaanalysis of published randomized controlled trials to assess the benefit of tamoxifen added to various single-agent or multiagent chemotherapy or biochemotherapy regimens. RESULTS: Six randomized trials met the inclusion criteria and were analyzed. These 6 trials involved a combined total of 912 patients. Of this number, 455 patients were randomized to receive tamoxifen added to chemotherapy or biochemotherapy regimens and 457 were randomized to receive chemotherapy or biochemotherapy without tamoxifen. The overall response rate was not improved significantly by the addition of tamoxifen to the chemotherapy regimen (odds ratio [OR], 1.16; 95% confidence interval [CI], 0.75-1.82; test for overall effect: P = 0.14). The results were not statistically significant for complete response (OR, 0.64; 95% CI, 0.33-1.25; test for overall effect: P = 0.19). CONCLUSIONS: The current metaanalysis demonstrated that tamoxifen does not improve the overall response rate, complete response rate, or survival rate when administered along with combined chemotherapy regimens. Currently, the strength of evidence does not support the use of tamoxifen in combination with other systemic chemotherapy for the treatment of metastatic melanoma.
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) | 0.001 | 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".