Evidence map›Paper›PMID 40332222›Full record

ReviewInternational journal of molecular sciences2025

The Revolution of Targeted Therapies in Thyroid Cancer Treatment: Present and Future Promising Anti-Cancer Drugs.

Sara Gil-Bernabé, Lucía García-DeLaFuente, Ginesa García-Rostán

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

3 authors.

Sara Gil-BernabéPathology Department, Faculty of Medicine, Valladolid University, 47003 Valladolid, Spain.ORCID 0000-0003-0199-6893
Lucía García-DeLaFuentePathology Department, Faculty of Medicine, Valladolid University, 47003 Valladolid, Spain.
Ginesa García-RostánPathology Department, Faculty of Medicine, Valladolid University, 47003 Valladolid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid cancer prevalence has increased in the last few decades. Whereas the majority of well-differentiated histotypes have effective therapeutic options, the most advanced cases lacked successful treatment until recent years. Genomic alterations have emerged as targets for new anti-cancer drugs. This molecular knowledge is gradually being translated into sophisticated approaches for the stratification, management, and therapies of patients with thyroid carcinomas. The genomic characterisation of tumours in clinical assistance serves as a tool for enhancing the prognostic assessment of patients with thyroid cancer and predicting their responses to the agents. The MAPK pathway is the most predominantly activated molecular route in this cancer. Several drugs have been developed to inhibit this pathway at different levels. However, the acquired resistance that emerges is the main problem in their use. Other strategies targeting not only driver mutations but also those that confer aggressive behaviour on tumours can be potential targetable options. Due to the new therapies, patients with the most aggressive histotypes have improved survival rates. Adverse events, although manageable, have a high prevalence among the current therapies. Selective inhibitors, immunotherapies, and the combination of both will play a pivotal role in the treatment and the improvements in overall survival in thyroid cancer patients.

Indexed as

Antineoplastic AgentsMolecular Targeted TherapyThyroid NeoplasmsHumansImmunotherapyProtein Kinase InhibitorsAntineoplastic AgentsProtein Kinase Inhibitorsanti-cancer drugtargeted therapiesthyroid

Identifiers

PMID40332222
PMCPMC12027515

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Registered trials

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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.