Frontiers in endocrinology · 2025
Gender, FT4 levels, T stage, and BMI as predictors of TSH levels in thyroid cancer patients.
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Zhang Sen, Niu Shuli, Zhou Ling
Аннотация
BACKGROUND: After initial treatment, levothyroxine (LT4) administration is necessary for thyroid cancer patients to achieve target thyroid-stimulating hormone (TSH) levels. However, the clinical efficacy of weight-based LT4 dosing has been suboptimal, highlighting the need to identify factors influencing the attainment of desired TSH levels and guide personalized treatment.
METHODS: We constructed a retrospective cohort comprising 215 patients diagnosed with thyroid cancer. The identification of factors influencing the attainment of expected TSH levels was accomplished through univariate and multivariate logistic regression analyses. Subsequently, we developed a nomogram based on these prognostic factors and performed internal validation using the bootstrap resampling method.
RESULTS: Univariate and multivariate logistic regression analyses were conducted to analyze the clinical and demographic parameters. A nomogram was constructed using bootstrap resampling to predict the risk of TSH suppression failure, which was validated. The nomogram demonstrated moderate discrimination in estimating the risk of TSH suppression failure, with a Hosmer-Lemeshow test p-value of 0.393 and a bootstrapped calibrated C-index of 0.757 (95% CI 0.687-0.814). The calibration curve indicated good consistency of the model, and decision curve analysis suggested that the nomogram had clinical utility.
CONCLUSION: Gender, preoperative serum free thyroxine (FT4) levels, T stage, and body mass index exhibit independent associations with the expected level of TSH. The established nomogram effectively predicts the risk of TSH suppression failure. Further research is warranted to investigate how these factors can be utilized in developing a personalized LT4 dosage calculator.
METHODS: We constructed a retrospective cohort comprising 215 patients diagnosed with thyroid cancer. The identification of factors influencing the attainment of expected TSH levels was accomplished through univariate and multivariate logistic regression analyses. Subsequently, we developed a nomogram based on these prognostic factors and performed internal validation using the bootstrap resampling method.
RESULTS: Univariate and multivariate logistic regression analyses were conducted to analyze the clinical and demographic parameters. A nomogram was constructed using bootstrap resampling to predict the risk of TSH suppression failure, which was validated. The nomogram demonstrated moderate discrimination in estimating the risk of TSH suppression failure, with a Hosmer-Lemeshow test p-value of 0.393 and a bootstrapped calibrated C-index of 0.757 (95% CI 0.687-0.814). The calibration curve indicated good consistency of the model, and decision curve analysis suggested that the nomogram had clinical utility.
CONCLUSION: Gender, preoperative serum free thyroxine (FT4) levels, T stage, and body mass index exhibit independent associations with the expected level of TSH. The established nomogram effectively predicts the risk of TSH suppression failure. Further research is warranted to investigate how these factors can be utilized in developing a personalized LT4 dosage calculator.