Metastasectomy and Stereotactic Body Radiotherapy for Colorectal Cancer With Liver and Lung Oligometastases: A Case Report of Complete Remission in a 96-Year-Old Patient
Bibliographic record
Abstract
We report a rare case of an extremely old colorectal cancer (CRC) patient who had complete remission after liver metastasectomy and stereotactic body radiotherapy (SBRT) to lung oligometastases (OM), with good quality of life and no evidence of recurrence 12 years after the initial diagnosis. An 83-year-old male patient had a right hemicolectomy for stage pT3 pN0 adenocarcinoma of the colon. Soon he was found to have liver metastasis treated with radiofrequency ablation and then liver metastasectomy with clear margins, followed by chemotherapy in the form of FOLFIRI for six months. Six years later, positron emission tomography (PET) showed 1.6 cm OM in the left upper lobe lung. He was not considered a good candidate for surgery. We offered him SBRT 48 Gy in four fractions every other day. The lesion disappeared with no recurrence in the same location on PET and serial computed tomography (CT) scans. Three years later, PET-CT found a new OM in the left lingular lung measuring 1.2 cm. A CT-guided lung biopsy confirmed invasive adenocarcinoma favoring OM from the CRC. SBRT planning failed due to its proximity to the heart. He accepted the longer course of conventional volumetric modulated arc therapy at 60 Gy in 15 fractions with daily cone-beam CT guidance. Again, he tolerated treatment very well with no significant side effects, despite his age. He did not require any chemotherapy or other systemic treatment in the last 11 years, so he did not experience any toxicities related to such treatment. This case is important to show that old age alone should not be considered a contraindication for metastasectomy and SBRT for CRC with liver and lung OM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".