Evidence map›Paper›PMID 40216704›Full record

ArticleEndocrine2025

Predictors of response to lenvatinib in advanced differentiated thyroid cancer: focus on the CONUT score.

Edoardo Talpacci, Silvia Morelli, Vincenzo Leone, Sonia Moretti, Miriam Paci, Vittorio Bini, Efisio Puxeddu

Abstract read
In one paragraph

Article in Endocrine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Role of nutritional (PNI, CONUT) and inflammatory indices (SII) in predicting lymph node metastasis and prognosis of thyroid cancer: a systematic review and meta-analysis.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Pooled it
  2. Observational
  3. Review
  4. Article
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

7 authors.

Edoardo TalpacciSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Silvia MorelliSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Vincenzo LeoneSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Sonia MorettiSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Miriam PaciSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Vittorio BiniSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
Efisio PuxedduSection of Internal Medicine and Endocrine and Metabolic Sciences, Department of Medicine and Surgery, University of Perugia, Perugia, Italy. efisio.puxeddu@unipg.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveLenvatinib is a multityrosine kinase inhibitor approved for progressive radioiodine refractory differentiated thyroid cancer (RAI-R-DTC). Despite its efficacy, most of the initial experiences showed global inferior results if compared with SELECT study. Baseline disease stages, previous systemic treatments and baseline patients' characteristics may affect response to therapy. The aim of our study was to review relevant clinical outcomes, identifying survival predictors, of a single center cohort of patients with advanced thyroid cancer treated with Lenvatinib.

methodsTwenty-two patients with progressive RAIR-R-DTC treated with Lenvatinib were retrospectively included. For each patient, we reviewed the main clinical baseline characteristics, including nutritional status. We evaluated the latter by using CONtrolling NUTritional status (CONUT) score. Clinical outcomes were overall survival (OS) and progression free survival (PFS).

resultsAt the time of analysis, 14 patients (63.6%) were alive with a median OS of 54 months (95% CI 20.35-87.65 months). Progression occurred in 16 patients (72.7%) with a median PFS of 21 months (95% CI 0-47.33 months). Nineteen out of 22 patients (86.4%) presented at least one adverse event (AE) of any grade. Baseline lower CONUT score significantly correlated with both longer PFS (HR 2.77- 95% CI 1.216-6.307, p = 0.015) and longer OS (HR 4.455-95% CI 1.211-16.391, p = 0.025). A significant longer survival was observed in patients with ECOG 0 compared to those with ECOG 1 and in the latter compared to ECOG 2 group (Log-rank test: p = 0.040). Conversely, higher baseline ECOG Performance Status (PS) correlated with higher severity of AEs (rs 0.468, p = 0.027). Finally, responder patients showed a significantly better PFS (HR 2.337-95% CI 1.091-5.006, p = 0.029).

conclusionWe confirmed the good efficacy of Lenvatinib treatment in progressive advanced RAI-R-DTCs showing the prognostic value of best tumor response, ECOG PS and CONUT score.

Indexed as

Antineoplastic AgentsPhenylurea CompoundsProtein Kinase InhibitorsQuinolinesThyroid NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedPrognosisProgression-Free SurvivalRetrospective StudiesTreatment OutcomeAntineoplastic AgentslenvatinibPhenylurea CompoundsProtein Kinase InhibitorsQuinolinesCONUT scoreLenvatinibProgression free survivalProgressive radioiodine-refractory differentiated thyroid cancer

Identifiers

PMID40216704
PMCPMC12227444

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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.