Neoadjuvant Immunotherapy Combined with Chemotherapy for Local Advanced Non-Small-Cell Lung Cancer in a Patient with a History of Breast Cancer: A Case Report
Bibliographic record
Abstract
Durvalumab consolidation therapy is the standard treatment after concurrent chemoradiotherapy for patients with surgically unresectable stage IIIA (N2) non-small-cell lung cancer (NSCLC). Neoadjuvant therapy followed by surgery could reduce locoregional and distant recurrence and improve the survival rate for surgically resectable NSCLC. However, the value of neoadjuvant therapy in locally advanced potentially resectable NSCLC remains controversial. Herein, we report a locally advanced potentially resectable NSCLC case with a history of breast cancer who achieved a pathologic complete response (pCR) after preoperative treatment with pembrolizumab and chemotherapy. A 50-year-old woman developed squamous cell carcinoma (SCC) (left lower lobe of the lung, stage IIIA-N2) after two years of chemotherapy and anti-HER2 therapy following a diagnosis of HER2-overexpressing breast cancer. Surgical resection was attempted despite an MDT classification as unamenable to curative surgical resection. After two cycles of neoadjuvant chemotherapy combined with anti-PD1 immunotherapy, the tumor significantly shrank, then the patient underwent a left lower lobectomy. Complete resection with negative margins (R0 resection) was achieved in the patient. The patient experienced grade 1-2 adverse effects and no grade 3 or worse adverse effects occurred. Cardiotoxicity did not occur in the patient despite prior anti-HER2 treatment for breast cancer. Our case study contributes to the existing evidence on the feasibility, efficacy, and safety of neoadjuvant immunotherapy combined with chemotherapy in locally advanced unresectable NSCLC. Furthermore, future studies are needed to determine which patients can benefit from immunoadjuvant therapy and the duration and course of preoperative and postoperative immunotherapy.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 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".