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Record W2794290503 · doi:10.2147/tcrm.s126143

Developments in the treatment of carcinoid syndrome – impact of telotristat

2018· review· en· W2794290503 on OpenAlexaff
David Chan, Simron Singh

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2018
Typereview
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersEMD SeronoIpsen Fund
KeywordsMedicineCarcinoid syndromeInternal medicine

Abstract

fetched live from OpenAlex

Carcinoid syndrome occurs in 20% of patients with neuroendocrine tumors, and serotonin is usually the main causative hormonal peptide. Carcinoid syndrome, and particularly diarrhea, can significantly impact patients' quality of life. Somatostatin analogs (SSAs) are the mainstay of treatment, but are unable to ameliorate symptoms in all patients due to dose-limiting side effects and tachyphylaxis. Telotristat is a novel oral inhibitor of tryptophan hydroxylase, which is the rate-limiting enzyme in serotonin synthesis. A Phase III placebo-controlled trial of telotristat etiprate (orally at 250 mg three times a day) showed a significant decrease in the frequency of bowel motions in treated patients with diarrhea from carcinoid syndrome. The main side effects were gastrointestinal symptoms, deranged liver function tests and depression. Treatment with 500 mg three times a day also decreased stool frequency, but was associated with more nausea and mood disturbances. Telotristat, therefore, represents a valuable option in the management of carcinoid syndrome diarrhea refractory to SSAs, and the US Food and Drugs administration approved its use for this indication in March 2017. However, its role in somatostatin-naïve patients and in the treatment of other carcinoid syndrome symptoms (flushing and abdominal pain) remains unknown. Further research should focus on these issues as well as the safety of continuing telotristat in the context of other systemic antineoplastic therapies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.187
GPT teacher head0.513
Teacher spread0.326 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations6
Published2018
Admission routes1
Has abstractyes

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