Quality of life issues faced by patients with keratinocyte cancer: A systematic review
Bibliographic record
Abstract
Introduction Keratinocyte carcinomas (KC), including basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), represent the most prevalent malignancy worldwide with a rapidly increasing incidence. While KC and its treatment can negatively impact patients quality of life (QoL), existing QoL instruments lack specificity for unique KC-related issues. This systematic review explores the relevant QoL issues pertinent to patients with KC. Methods Literature from Ovid MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases from 1946 to January 2023 was systematically reviewed. Two independent reviewers screened and extracted studies of all designs discussing KC-specific QoL issues. Results The systematic review identified prevalent QoL issues in the literature. Some generic QoL-related issues are covered by more general cancer QoL instruments that are not site specific to KC, such as the EORTC QLQ-C30. These include pain, functioning, daily activities, work, leisure time, and social and family relationships. More KC-specific issues include the impact of cosmetic outcomes on QoL, such as scarring, skin pigmentation change, embarrassment, distress, and social withdrawal. Improved sun awareness, including increased sunscreen use, avoidance of outdoor activities, and sun-protective clothing usage, emerged as common changes in behaviour. These issues may result from both the disease and the treatment. Conclusions This review has identified multiple KC-specific QoL issues, highlighting need for a tailored QoL instrument to measure these KC-specific issues. As the landscape of KC research and treatment modalities evolve, a gap persists in terms of a standardized QoL measurement for both clinical and research contexts. A new QoL instrument needs to be developed which is better tailored to the needs of patients with KC.
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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".