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    Home > Active Ingredient News > Endocrine System > European Radiology: Prediction of efficacy of thermal ablation in the treatment of primary hyperparathyroidism

    European Radiology: Prediction of efficacy of thermal ablation in the treatment of primary hyperparathyroidism

    • Last Update: 2022-10-19
    • Source: Internet
    • Author: User
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    Primary hyperparathyroidism (PHPT) is a common endocrine disorder characterized by
    high blood calcium and elevated PTH levels.
    Its incidence is 21 per 1,000 women aged 55-75, equivalent to 0.
    3% of the total European population, and the United States has an incidence of up to 0.
    86%, affecting a ratio of 1:4
    males.

    Ultrasound-guided thermal ablation therapy for PHPT is a new minimally invasive treatment modality, which has the advantages of
    less trauma, short operation time, and only local anesthesia.
    However, not all patients with PHPT benefit from ablation therapy
    .
    Studies have shown that about 10-15% of patients experience relapse after ablation, marking the failure
    of ablation therapy.
    Therefore, achieving efficacy while ensuring safety and aesthetics has become an important issue
    .
    Given this situation, there is an urgent need to classify the risk of recurrence of PHPT based on preoperative characteristics and to identify patients
    most likely to benefit from thermal ablation therapy.

    At present, there is a lack of simple and reliable tools to effectively predict the outcome
    of thermal ablation therapy in patients with PHPT.
    A study published in the journal European Radiology evaluated the relationship between PTH and PHPT thermal ablation outcomes and established and validated a predictive ablation outcome model that can be used clinically to identify
    PHPT patients who could benefit from thermal ablation therapy.

    A total of 171 patients were screened, of whom 148 (86.
    5%) were eligible and divided into development groups (n = 104) and external validation groups (n = 44).

    The potential relationship between the PTH-based classification
    model and patient cure rates was initially evaluated in the primary cohort and then validated
    in the external validation cohort.
    A nomogram is calculated by a logistic regression model
    .

    PTH<269.
    1 pg/mL or ≥269.
    1 pg/mL were generated in the training cohort as the cut-off for optimal prognosis, and patients were divided into low- and high-risk groups
    .
    Patients with PTH levels < 269.
    1 pg/mL in the training cohort had higher cure rates than patients with PTH levels ≥ 269.
    1 pg/mL (P<0.
    001).

    Across all cohorts, PTH levels remained the strongest predictor of
    cure rates.
    Also,
    nomograms
    based on PTH levels.
    Cure rates were predicted in the training cohort and performed well in the external validation cohort (AUC: 0.
    816, 95% CI 0.
    703 to 0.
    930; AUC: 0.
    816, 95% CI 0.
    677 to 0.
    956).


    Figure
    Top 11 features selected using XGBoost and corresponding variable importance scores

    This study shows that a newly developed PTH-based classification model can identify
    PHPT patients with a low risk of recurrence after thermal ablation.
    PTH levels prior to ablation will facilitate preoperative counseling of patients and assist clinicians in selecting treatment options
    .

     

    Original source:

    Yang Liu,Chengzhong Peng,Huihui Chai,et al.
    Predicting ultrasound-guided thermal ablation benefit in primary hyperparathyroidism.
    DOI:10.
    1007/s00330-022-08898-x

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