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1000 Titel
  • Validation of two predictive models for survival in anaplastic thyroid cancer (ATC)
1000 Autor/in
  1. Käsmann, Lukas |
  2. Nieto, Alexander |
  3. Rennollet, Robert |
  4. Gurtner, Ralph |
  5. Oliinyk, Dmytro |
  6. Augustin, Teresa |
  7. Koehler, Viktoria Florentine |
  8. Neu, Maria |
  9. Belka, Claus |
  10. Spitzweg, Christine |
  11. Rauch, Josefine |
1000 Verlag
  • BioMed Central
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-11-29
1000 Erschienen in
1000 Quellenangabe
  • 24(1):1477
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12885-024-13217-2 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11606035/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>The prognosis of patients with anaplastic thyroid cancer (ATC) remains dismal. A small portion of patients experience longterm survival and need to be identified before treatment allocation. Survival scores may guide clinicians making more informed decisions about treatment options and improve the understanding of patients’ prognosis. The aim of this study was to validate two prognostic scores using an independent dataset to analyze which prognostic index is superior in discriminating survival.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>Thirty-four patients with histologically confirmed ATC diagnosed between January 2009 and December 2019 were consecutively treated at our department and evaluated. Next generation sequencing was performed in 7 (21%) patients, but no druggable mutation was found. 50% of all patients received surgery and 56% were treated with chemoradiotherapy. The median radiation dose in equivalent dose in 2 Gy fractions (EQD2) was 50 Gy (SD:21 Gy). The study compared the discrimination of the Sugitani Prognostic Index (SPI) and the Marchand-Crety Prognostic Score (MCPS) using concordance statistics, area under the receiver-operating characteristics curve (AUC), net reclassification index, and integrated discrimination improvement for 6-month survival.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>The median survival of the entire cohort was 5 months (range: 1-133). The AUC for 6-month survival was 0.85 (95% confidence interval [CI]:0.72–0.97) for SPI and 0.69 (95% CI: 0.56–0.83) for MCPS (<jats:italic>p</jats:italic> &lt; 0.0001). Using the net reclassification index (NRI), 73% of patients were correctly reclassified using SPI instead of MCPS for 6-month survival (<jats:italic>p</jats:italic> = 0.0237).</jats:p> </jats:sec><jats:sec> <jats:title>Conclusion</jats:title> <jats:p>The SPI was more accurate than the MCPS to determine patients’ life expectancies and should be recommended for clinical guidance and treatment allocation. In the last decade, comprehensive genetic profiling of actionable mutations in ATC has become vital to guide targeted therapy.</jats:p> </jats:sec>
1000 Sacherschließung
lokal Female [MeSH]
lokal Thyroid Carcinoma, Anaplastic/mortality [MeSH]
lokal Aged, 80 and over [MeSH]
lokal Aged [MeSH]
lokal Adult [MeSH]
lokal Humans [MeSH]
lokal Thyroid Carcinoma, Anaplastic/pathology [MeSH]
lokal Anaplastic thyroid cancer
lokal Retrospective Studies [MeSH]
lokal Middle Aged [MeSH]
lokal Multimodal treatment
lokal Thyroid Neoplasms/genetics [MeSH]
lokal Prediction
lokal Thyroid Neoplasms/pathology [MeSH]
lokal Thyroid Neoplasms/therapy [MeSH]
lokal Survival
lokal Male [MeSH]
lokal ROC Curve [MeSH]
lokal Research
lokal Prognosis [MeSH]
lokal Thyroid Neoplasms/mortality [MeSH]
lokal Score
lokal Thyroid Carcinoma, Anaplastic/genetics [MeSH]
lokal Thyroid Carcinoma, Anaplastic/therapy [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/S8Okc21hbm4sIEx1a2Fz|https://frl.publisso.de/adhoc/uri/TmlldG8sIEFsZXhhbmRlcg==|https://frl.publisso.de/adhoc/uri/UmVubm9sbGV0LCBSb2JlcnQ=|https://frl.publisso.de/adhoc/uri/R3VydG5lciwgUmFscGg=|https://frl.publisso.de/adhoc/uri/T2xpaW55aywgRG15dHJv|https://frl.publisso.de/adhoc/uri/QXVndXN0aW4sIFRlcmVzYQ==|https://frl.publisso.de/adhoc/uri/S29laGxlciwgVmlrdG9yaWEgRmxvcmVudGluZQ==|https://frl.publisso.de/adhoc/uri/TmV1LCBNYXJpYQ==|https://frl.publisso.de/adhoc/uri/QmVsa2EsIENsYXVz|https://frl.publisso.de/adhoc/uri/U3BpdHp3ZWcsIENocmlzdGluZQ==|https://frl.publisso.de/adhoc/uri/UmF1Y2gsIEpvc2VmaW5l
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  • DeepGreen-ID: 6379c3f7e01840e49c78784d980a044d ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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  1. Klinikum der Universität München |
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1000 Dateien
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    1000 Förderer Klinikum der Universität München |
    1000 Förderprogramm -
    1000 Fördernummer -
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1000 Erstellt am 2025-07-07T00:55:05.258+0200
1000 Erstellt von 322
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1000 Zuletzt bearbeitet 2025-07-30T01:17:25.888+0200
1000 Objekt bearb. Wed Jul 30 01:17:25 CEST 2025
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