Hormone Therapy

Efficacy of machine learning to identify clinical factors influencing levothyroxine dosage after total thyroidectomy.

TL;DR

Machine learning algorithms indicated that race, ethnicity, lifestyle and comorbidity factors also may impact levothyroxine dosing in post-thyroidectomy patients with benign conditions, beyond the known factors of weight, sex, age, and BMI.

Key Findings

The XGBoost machine learning model achieved higher accuracy than the standard weight-based dosing formula in predicting adequate levothyroxine dosage.

  • XGBoost model achieved 61.0% accuracy in predicting adequate dosage
  • Standard formula of 1.6 mcg/kg/day achieved only 47.0% accuracy
  • Difference was statistically significant (p < 0.05)
  • Study included 487 patients who underwent total or completion thyroidectomy with benign pathology and achieved euthyroid state

Non-Caucasian race was associated with levothyroxine dosing requirements in Poisson regression analysis.

  • Non-Caucasian race was significantly associated with dosing (p < 0.05)
  • Study population was 39.0% White, 53.0% Black, 2.7% Hispanic, 1.4% Asian, and 3.9% Other
  • Race was identified as a factor beyond the known predictors of age, sex, and weight

Routine alcohol use was positively associated with levothyroxine dosage requirements.

  • Routine alcohol use had a positive estimate of 0.03 (p = 0.02) in Poisson regression
  • This suggests patients with routine alcohol use required higher levothyroxine doses
  • Alcohol use was identified as a novel lifestyle factor influencing dosing

Osteoarthritis was negatively associated with levothyroxine dosage requirements.

  • Osteoarthritis had an estimate of -0.10 (p < 0.001) in Poisson regression
  • This suggests patients with osteoarthritis required lower levothyroxine doses
  • Osteoarthritis was identified as a novel comorbidity factor influencing dosing

Known clinical factors including age, sex, and weight were confirmed to be significantly associated with levothyroxine dosing in Poisson regression.

  • Age was negatively associated with dosing (estimate = -0.003, p < 0.001), indicating older patients require lower doses
  • Female sex was negatively associated with dosing (estimate = -0.06, p < 0.001), indicating females require lower doses
  • Weight was positively associated with dosing (estimate = 0.01, p < 0.001), indicating heavier patients require higher doses

The study population consisted predominantly of female and Black patients who underwent total or completion thyroidectomy for benign pathology.

  • 487 patients were included in the analysis
  • Mean age was 54.1 ± 14.1 years
  • 86.0% were female
  • 53.0% were Black and 39.0% were White
  • This was a retrospective study design

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Citation

Zheng H, Lai V, Lu J, Hu D, Kang J, Burman K, et al.. (2023). Efficacy of machine learning to identify clinical factors influencing levothyroxine dosage after total thyroidectomy.. American journal of surgery. https://doi.org/10.1016/j.amjsurg.2022.11.025