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The impact of surgery on patients with VHL-associated tumors: An international patient survey.

2023· article· en· W4379283421 on OpenAlexaboutno aff
Murali Sundaram, Christian Atkinson, Joshua R. Mann, Charley Cooper, Gavin Taylor‐Stokes, Othon Iliopoulos

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
FundersMerck
KeywordsMedicineRenal cell carcinomaInternal medicineHemangioblastomaSurgeryPediatrics

Abstract

fetched live from OpenAlex

4517 Background: Von Hippel-Lindau syndrome (VHL) is a rare hereditary neoplastic disorder caused by mutations in the VHL gene. Treatment (tx) options for patients are limited to multiple surgeries dispersed between regular scans, watchful waiting and txs that preserve organ function. Methods: An international, cross-sectional survey comprising patients in the United States (US), Canada (CA), the United Kingdom (UK), France (FR), and Germany (DE) was conducted. Patients were recruited via the VHL Alliance; data were collected between Dec 2021 and May 2022. For inclusion, patients must have renal cell carcinoma (RCC), pancreatic neuroendocrine tumors (pNET), and/or central nervous system hemangioblastoma (CNS-Hb). Data collected included demographics, impact of most recent surgery on aspects of condition (1-7 scale 1 being greatly worsened and 7 being greatly improved), tx goals (top 3 goals from a list of 11), and patient preference in treatment. Patients were presented two scenarios “watch and wait” and potentially need surgery, or “take a once-daily pill” to delay a potential surgery. Results: 220 patients (68.2% female, median age 40.0, median disease duration 15.8 years) in the US (n=108), CA (n=37), the UK (n=21), FR (n=3), and DE (n=51) completed the study. 146 patients reported RCC (66.4%), n=122 reported pNET (55.5%), and n=190 reported CNS-Hb (86.4%). Among the top 4 symptoms experienced by patients were kidney cysts (n=82, 37.3%), numbness (n=59, 26.8%), dizziness (n=56, 25.5%), and fatigue/low energy (n=54, 24.5%). 205 (93.2%) patients had experienced surgery; n=171 (77.7%) had experienced multiple surgeries (median number of surgeries, 4.0). 166 patients recorded data on their most recent surgery. Of these, patients reported that their most recent surgery worsened (scored 1-3) their fatigue (51.8%), mental health (51.2%), and ability to go about daily life (45.2%). 47.3% of patients selected reduce the number of surgeries as a top tx goal, 46.4% selected being able to go about life as usual, 36.8% delay the need for surgery, and 33.2% improved quality of life. 73% of patients indicated they would prefer to take a pill which would possibly delay the time until surgery, rather than watch and wait to see if the tumor would grow. Conclusions: Surgery negatively impacts the lives of patients, leading to a worsening in their fatigue, mental health, and ability to go about daily life. Almost half of patients would like a treatment that reduces the number of surgeries, and over a third would like a treatment that delays the need for surgery. Nearly three quarters of patients would prefer to take a pill that might delay the need for surgery. Tx options that reduce the need for surgery would benefit this patient group.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.085
GPT teacher head0.429
Teacher spread0.344 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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