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October 23, 2025Future Oncology

A clinical model for growth rate-driven prediction of histological subtypes in invasive pulmonary adenocarcinomas

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Authors

FZFeiyang ZhongZLZhenxing LiuLWLijun Wu

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Overview

Nomogram predicts high-grade adenocarcinoma components from tumor growth rate and clinical characteristics, indicating better diagnostics for lung cancers.

Key Points

  • Tumor growth rate predicts high-grade components in adenocarcinomas, enhancing diagnostic accuracy.
  • Nomogram developed using clinical and radiological characteristics in lung adenocarcinomas shows promise.
  • Assessing growth rate can improve prediction of histological subtypes compared to existing methods.
  • The findings may enable tailored approaches in lung cancer treatment depending on subtype specifics.

Cite This Study

Zhong et al. (2025) studied this question.

synapsesocial.com/papers/68fa1210f9f8b44535bfcf66https://doi.org/10.1080/14796694.2025.2577628
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