REVIEW Primary Care Review of Actinic Keratosis and Its Therapeutic Options: A Global Perspective
Bibliographic record
Abstract
The Author(s) 2015. This article is published with open access at Springerlink.com Actinic keratosis (AK) is a common skin condition caused by long-term sun exposure that has the potential to progress to non-melanoma skin cancers. The objective of this review is to examine the therapeutic options and management of AK globally, particularly in Australia, Canada, and the United Kingdom. Despite its potentially malignant nature, general awareness of AK is low, both in the general population and in the primary health care setting, especially in countries with low incidence. There is no standard therapeutic strategy for AK; it is treated through a variety of lesion-directed or field-directed therapies or a combination of both. A variety of treatment options are used depending on the experience of the primary care physician, the pathology of the lesion, and patient factors. Studies have shown that the physicians do not always use the optimal treatment option because of a lack of knowledge. The higher incidence of AK in fair-skinned people in Australia has resulted in well-established management strategies and guidelines for its treatment, compared with countries with lower incidence. It is essential to raise the awareness of AK because of its potential to progress to invasive squamous cell carcinoma. Primary care physicians are often the first to see this condition in their patients and are perfectly placed to educate the public and raise awareness. It is therefore desirable that their education and knowledge about AK and its treatment are up to date.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".