UK clinical practice guidelines for the management of patients with constitutional <i>POT1</i> pathogenic variants
Bibliographic record
Abstract
Constitutional or germline pathogenic variants (GPVs) in protection of telomeres 1 (POT1 ) are associated with a variety of tumours resulting in the recognition of POT1-tumour predisposition syndrome (POT1-TPDS). These tumours may include cutaneous melanoma, angiosarcoma, haematological malignancy and brain tumours. Due to the rarity of POT1 GPVs and limited available data, the overall lifetime cancer risks for individuals with POT1-TPDS are unclear. Furthermore, there is scant evidence to support the role of surveillance in early cancer detection in this patient group. A recent international publication suggested a surveillance protocol similar to that used in Li-Fraumeni Syndrome (LFS) could be offered to POT1 pathogenic variant carriers, particularly where there are LFS-like features. However, current evidence for POT1-TPDS is not supportive of an equivalent lifetime cancer risk. Given the inclusion of POT1 in the National Test Directory in England and the need for UK-based guidance, an expert group undertook a literature review to assess the phenotypic spectrum of POT1-TPDS and to provide lifetime risk estimates of POT1 -associated cancers. The available evidence was shared with a small working group of experts that included clinical geneticists, dermatologists, sarcoma specialists, haematologists and radiologists to cover all aspects of the cancers most commonly associated with POT1-TPDS. Following structured expert group discussions, we achieved consensus on best practice recommendations for a POT1-TPDS UK management protocol.
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 | 0.013 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.023 |
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".