Treatment for Recurrent Differentiated Thyroid Cancer: A Canadian Population Based Experience
Bibliographic record
Abstract
INTRODUCTION: Management of recurrent differentiated thyroid cancer (DTC) may include surgery, radioactive iodine (RAI), and external beam radiotherapy (EBRT). Systemic therapy may also be offered for RAI-refractory DTC. The study objective was to review patterns of practice in British Columbia (BC) for treatment of recurrent DTC, assess rates of RAI-refractory disease, and evaluate outcomes. METHODS: BC Cancer provides cancer care to a population of 4.6 million. A retrospective review of all patients with DTC stage I-IVB disease referred to BC Cancer from 2009 to 2013 was conducted. Patient and DTC characteristics, locoregional and distant recurrence, surgical management, RAI, EBRT, and systemic therapy details were retrospectively collected. Relapse-free survival (RFS), overall survival (OS), and disease-specific survival (DSS) were calculated using the Kaplan-Meier method. RESULTS/DISCUSSION: Some 1062 DTC patients were identified. Median follow-up was 4.1 years. Baseline characteristics: female 74%, median age 50, papillary/follicular/Hurthle cell 92%/6%/2%. Stage at presentation: I 60%, II 8%, III 22%, IVA/IVB 10%. Locoregional and/or distant recurrence occurred in 136 patients (13%). Locoregional recurrence (n=118) was treated with surgery +/- RAI or EBRT 48%, RAI +/- EBRT 40%, EBRT alone 1%, 11% were observed without treatment. Some 27 patients had a second cancer recurrence. Some 37 patients (3%) developed distant metastatic disease and common sites of distant metastases were: lung 76%, bone 30%, and liver 8%. Some 27 cases (2%) were deemed RAI-refractory. Some six patients (0.6%) received systemic therapy with a vascular endothelial growth factor tyrosine kinase inhibitor (VEGF TKI). Five-year RFS was calculated to be 82%, OS 95%, and DSS 98% for the study population. CONCLUSIONS: In our population-based study cohort, 87% of patients were rendered disease-free by primary disease management. Multi-modality treatment of locoregional recurrence facilitated disease-free status in the majority of patients (67%). RAI-refractory disease developed in 2% of patients and despite a significant number of metastatic recurrences, only a small number of patients received systemic therapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".