PD-1 Inhibitor Maintenance Therapy Combined Iodine-125 Seed Implantation Successfully Salvage Recurrent Cervical Cancer after CCRT: A Case Report
Bibliographic record
Abstract
Cervical cancer is the fourth most common cancer in females worldwide. Patients with stage III and IV cervical cancer based on the Federation of Gynecology and Obstetrics (FIGO) classification have higher recurrence rates. Because of organs at risk (OAR) protection and the low indication rate of salvage surgery, the choice of treatment is always challenging. Systemic chemotherapy is palliative and can be performed in conjunction with surgery or radiotherapy; however, it has no significant benefit to survival. Brachytherapy and stereotactic body radiotherapy (SBRT) are characterized by extremely high radiation doses applied to tumor cells while sparing the normal tissues. Several studies have investigated the efficacy of these technologies in recurrent cervical cancer and showed promising results. The immune checkpoint inhibitors approach was also investigated and showed promising results too. Herein, we report a case of a patient with cervical cancer that recurred five months after adjuvant chemotherapy and concurrent chemoradiotherapy. The disease prognosis after interstitial implantation brachytherapy (IIB) was determined. Then, the patient underwent radioactive 125I-seed implantation combined with PD-1 inhibitor treatment. The patient exhibited a partial response after seed implantation, and up to now, the duration of this partial response was 24 months.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 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".