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Record W2313590912 · doi:10.1158/1538-7445.am2011-4677

Abstract 4677: The differences among various age groups of oral cancers in British Columbia

2011· article· en· W2313590912 on OpenAlexaffabout
Tarinee Lubpairee, Lewei Zhang, Miriam P. Rosin, Catherine F. Poh

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsMedicineAge groupsCancer registryCancerIncidence (geometry)Basal cellInternal medicinePopulationDemographyTongueLongitudinal studyPathology

Abstract

fetched live from OpenAlex

Abstract Oral squamous cell carcinoma (OSCC) is a disease commonly in those who are older and/or heavily smoke. However, the incidence of younger group is increasing world-wide. Research to understand this shift can have significant impact on oral cancer control. Objectives: 1) To determine the characteristics of OSCC in different age groups in a longitudinal study and 2) To compare the differences among groups. Methods: From 1990 to 2008, we recruited 536 OSCCs for the BC Oral Cancer Prediction and Longitudinal (OCPL) Study. We have arbitrarily put them into groups based on the age at initial OSCC diagnosis: 43 (8%) were equal to or under age 40 years (Young group); 212 (40%) were diagnosed between age 50 to 65 (Conventional group); 91 (17%) were age 75 or older (Old group). To better define the difference among various age groups, we excluded those between ages 41-49 (12%) and 66-74 (24%). Demographics, smoking habit, clinicopathological features of the lesion, treatment modalities, and outcome data were collected. The data were also compared with those from the BC Cancer Registry in the same period years to determine the representativeness of the BC population. Results: The Young OSCC from the OCPL Study had no significant differences from those in Registry in gender, anatomical location, tumor staging, and differentiation. When compared to the Conventional group, the Young group showed less Caucasian (66% vs. 86%, P = 0.005), less smokers (35% vs. 77%, P < 0.0001), tongue predilection (88% vs. 51%, P < 0.0001), more treated with combined chemotherapy (12% vs. 4%, P = 0.05), and better prognosis in distant metastases or death (16% vs. 47%, P < 0.0001). When compared to Conventional group, the Old group had more cancers involving more than one anatomical site (P = 0.028) and showed frequently distant metastasis (P = 0.0003). When comparing between the Young and Old groups, we found that the Old group had more Caucasians (86% vs. 66%, P = 0.02), ever smokers (66% vs. 35%, P = 0.001), less tongue location (42% vs. 88%, P < 0.0001) and significantly worse clinical outcome in local recurrence, regional recurrence and distant metastasis. Conclusion: Various age groups of early-staged oral cancer show different clinical behaviors. Nonsmokers and tongue-located tumor characterize the Young group which has a better prognosis in survival. More molecular studies are needed for better understanding the underlying driven force. An attempt to characterize the difference using-molecular tools is ongoing. This might shed the light in difference among different age groups. (Supported by grant R01 DE17013 from the National Institute of Dental and Craniofacial Research and grant CCSRI-20336 from Canadian Cancer Society Research Institute) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4677. doi:10.1158/1538-7445.AM2011-4677

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.149
GPT teacher head0.387
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes2
Has abstractyes

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