The pattern of lip cancer occurrence over the 1990–2011 period in public hospitals in <scp>M</scp>adrid, <scp>S</scp>pain
Bibliographic record
Abstract
BACKGROUND: Some regions of Spain along with Canada and Australia have the highest rates of lip cancer in the world. The objective of this study was to examine the trends in the pattern of occurrence of lip cancer in Madrid, Spain. METHODS: Data were extracted from the Central Tumour Registry of Madrid, between 1990 and 2011. Variables examined were age, sex, topographic and morphological location and tumour histology. Two consecutive periods, 1990-2001 and 2002-2011, were studied by descriptive and analytical methods, and the data from the two periods were statistically compared. RESULTS: A total of 881 cases were registered during the period 1990-2011. Comparing data between the two periods (1990-2001 and 2002-2011), subtle variations in age, histology and location were noted. Gender ratios remained constant. The mean age increased from 66.3 to 69.7 years (P < 0.05). In the second period, the histological distribution showed an increase in frequency of basal cell carcinoma, from 2.1% to 4.7%, while the frequency of squamous cell carcinomas remained constant. Basal cell carcinoma no longer predominantly occurred in women, decreasing from 80% to 21.1% (P < 0.001). The distribution by gender of squamous cell carcinoma had become more equal due an increase in its frequency in women (P < 0.001). Frequency of tumours on lip mucosa and commissure had increased between the two periods (P < 0.004). CONCLUSIONS: The pattern of lip cancer reported to Public Hospitals of Madrid is changing: declining rates are noted since 2001-02. However, it is necessary to monitor these data to confirm the observed trends in future years.
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 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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".