Ki‐67 index enhances the prognostic accuracy of the urothelial superficial bladder carcinoma risk group classification
Bibliographic record
Abstract
Approximately 80% of bladder tumors are urothelial superficial papillary carcinomas (USPC). Despite a generally good prognosis, these tumors have a strong propensity to recur and about 1/3 of them compared to disease progression. Histological assessment of these superficial tumors is not sufficiently discriminator in predicting prognosis; therefore, we decided to evaluate the prognostic significance of p53 and Ki-67 immunoexpression in low-grade (GI-II) USPC in order to predict the potential outcome of these tumors. P53 and Ki-67 immunoexpression were studied in function of recurrence-free and progression-free survival in 159 primary superficial bladder tumors. A prognostic risk model based on grade, stage and multifocality was also evaluated. P53 accumulation was significantly related to tumor progression (p=0.006). High Ki-67 index (>/=18%) and multifocality were significantly related to recurrence (both p=0.0001) and progression-free survival (both p=0.0001) and were independent prognostic factors in the multivariate analysis. The prognostic risk model based on grade, stage and multifocality was not an efficient discriminator of outcome. Adding the Ki-67 index into the risk model, single pTa/T1-GI Ki-67 positive tumors, usually classified as low risk, were reclassified as of intermediate risk. After this reclassification, the risk group model identified a subgroup of pTa/T1-G1 with a high risk of recurrence and progression. Ki-67 index is a reliable prognostic marker in urothelial superficial bladder carcinoma and, when included into a risk profile classification of the low-grade USPC, the accuracy of the prognostic discrimination is enhanced.
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) | 0.000 | 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".