Evidence map›Paper›PMID 35501552›Full record

ReviewCurrent treatment options in oncology2022

High-Dose Somatostatin Analogs for the Treatment of Neuroendocrine Neoplasms: where are we Now?

Teresa Alonso-Gordoa, Ray Manneh, Enrique Grande, Javier Molina-Cerrillo

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Teresa Alonso-GordoaMedical Oncology Department, Hospital Universitario Ramón y Cajal, 28034, Madrid, Spain. talonsogordoa@gmail.com.ORCID 0000-0002-8966-7236
Ray MannehMedical Oncology Department, University Hospital 12 de Octubre, 28041, Madrid, Spain.
Enrique GrandeMedical Oncology Department, MD Anderson Cancer Center Madrid, 28033, Madrid, Spain.
Javier Molina-CerrilloMedical Oncology Department, Hospital Universitario Ramón y Cajal, 28034, Madrid, Spain.
Universidad de Alcalá · ESMD Anderson Cancer Center Madrid · ESPopular University of Cesar · CO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

opinion statementNeuroendocrine tumors (NET) represent a complex and heterogeneous group of malignancies arising from the diffuse endocrine cells and other cells derived from the neural crest. Advanced disease is observed at diagnosis in more than one-third of patients. Somatostatin analogs (SSA) are the cornerstone in advanced well-differentiated NET treatment. Unfortunately, most patients will eventually develop resistance to SSA treatment by different mechanisms that are not fully understood. In some cases of refractory carcinoid syndrome or progressive disease, the increase of SSA dose may help to reach out a symptomatic and/or tumor growth control. The clinical evidence behind above-label SSA administration is limited and should be individualized and discussed patient by patient. Some questions regarding high-dose SSA use are unsolved, such as the optimal dose to use, the frequency of administration, or the need of deepen molecular understanding that could help to adequately select patients for this approach.

Indexed as

Malignant Carcinoid SyndromeNeuroendocrine TumorsHumansSomatostatinSomatostatinHigh-dose somatostatin analogsNeuroendocrine tumorsRadionuclidesRefractory carcinoid syndromeSomatostatin receptors

Identifiers

PMID35501552
OpenAlexW4225281129

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.