Method for evaluating osteoporotic fracture risk of thyroid cancer postoperative TSH inhibition treatment

Abstract

The invention relates to the technical field of diagnosis of thyroid cancer postoperative TSH inhibition treatment patient osteoporosis risk assessment, in particular to a thyroid cancer postoperative TSH inhibition treatment osteoporosis fracture risk assessment method, which comprises the following steps: step 1, determining a research object, and setting an inclusion standard and an exclusion standard of the assessment method for the research object; 2, confirming a research method according to the step 1, and refining a specific inspection method of a specific part; and 3, according to the check result in the step 2, determining an FRAX calculation and TSH level weighted assignment method. In the medical evaluation process, all evaluation modes are based on statistics, a new FRAX algorithm assigned according to the TSH level is used for evaluating the osteoporosis fracture risk of a patient subjected to differentiated thyroid cancer postoperative TSH inhibition treatment, the fracture prediction value of an FRAX tool on a specific crowd is optimized, and the risk of osteoporosis of the patient subjected to differentiated thyroid cancer postoperative TSH inhibition treatment is improved. Therefore, the evaluation accuracy of the subject to the specific crowd and the pertinence of evaluating the coverage crowd range are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of postoperative nursing for thyroid cancer, and in particular to a method for evaluating the risk of osteoporotic fractures in TSH suppression therapy after thyroid cancer surgery. Background Art

[0002] Thyroid cancer is a common malignant tumor of the head and neck, accounting for 1% to 2% of all malignant tumors in the body. Surgery is a common treatment for thyroid cancer. In the postoperative care of thyroid cancer, it is often necessary to use methods to assess the risk of osteoporotic fractures after TSH suppression therapy for thyroid cancer.

[0003] After searching, the existing fracture risk assessment tool is an assessment tool for assessing the fracture risk of major parts and hips within 10 years in people over 50 years old. Patients who receive thyroid stimulating hormone suppression therapy after differentiated thyroid cancer surgery are a high-risk group for osteoporosis. Patients with differentiated thyroid cancer need to take levothyroxine for TSH suppression therapy after surgery, which makes this group of people at high risk of osteoporotic fractures, and there is a strong dose-duration response relationship between the use of levothyroxine and the risk of osteoporosis. The bone density of patients who receive TSH suppression therapy after thyroid cancer surgery is significantly reduced, and the risk of major osteoporotic fractures and hip fractures are significantly increased. Therefore, there are a certain number of problems. For example, during the postoperative observation process, the fracture risk adopted by the existing FRAX tool does not include the risk factor of TSH suppression therapy after differentiated thyroid cancer surgery, and compared with the BMD tool, it can more effectively identify high-risk individuals. Therefore, the FRAX tool is not suitable for this population. In order to solve the above technical problems, we designed a method to assess the risk of osteoporotic fractures after TSH suppression therapy after thyroid cancer surgery. Summary of the invention

[0004] The purpose of the present invention is to provide a method for evaluating the risk of osteoporotic fractures in TSH suppression therapy after thyroid cancer surgery, which has the advantages of good evaluation effect and a wide evaluation range, and solves the problems of general evaluation effect and low coverage of the evaluation range.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for evaluating the risk of osteoporotic fractures in TSH suppression therapy after thyroid cancer surgery, comprising the following steps:

[0006] Step 1: Determine the research subjects and establish the inclusion and exclusion criteria of the evaluation method for the research subjects;

[0007] Step 2: Confirm the research method according to step 1 and refine it to the specific research and inspection method of specific parts;

[0008] Step 3: Establish the FRAX calculation and TSH weighted scoring method based on the results of the study in step 2;

[0009] Step 4: Carry out classification inspection and comparison based on the inspection results of step 3;

[0010] Step 5: Perform multiple rechecks and verifications based on the comparison results of step 4;

[0011] Step 6: Summarize the conclusions obtained from all the above steps.

[0012] Preferably, the detailed process in step 1 includes the following steps:

[0013] A: A total of 64 patients with differentiated thyroid cancer who underwent thyroidectomy and took oral levothyroxine tablets for TSH suppression therapy in our hospital from October 2021 to May 2022, and 30 healthy people were collected. Among them, there were 40 males and 24 females in the diseased group. All patients were over 20 years old and had hip bone density measurements, all expressed as T values ​​(the T value was obtained according to the reference standard, that is, the World Health Organization standard T index provided by the NHANESⅢ database covering white women aged 20-29). During the consultation, the doctor conducted a questionnaire survey on the patients and collected the general information and medical history of the patients, mainly including gender, age, height, weight, operation time, history of fragility fracture, history of rheumatoid arthritis, previous history of chronic diseases (hypertension, diabetes, coronary heart disease, etc.), history of hip fracture of parents, smoking, drinking, history of hormone use, secondary osteoporosis, history of thyroid and parathyroid dysfunction, etc. This study was conducted with the informed consent of the included subjects and has been approved by the Research Ethics Committee of the 960th Hospital of the People's Liberation Army (approval number: (2022) Research Ethics No. (45));

[0014] B: Establishing inclusion and exclusion criteria for evaluation methods

[0015] 1. Inclusion criteria

[0016] ① Patients diagnosed with differentiated thyroid cancer who have undergone TSH suppression therapy for at least 6 months after thyroidectomy and have undergone hip bone density examination;

[0017] ② Aged 20 or above, with normal communication and comprehension abilities, able to carry out normal activities and adhere to follow-up;

[0018] ③After fully understanding and informed consent, voluntarily participate in this study and sign the informed consent form.

[0019] 2. Exclusion criteria

[0020] ① Patients with thyroid and parathyroid dysfunction, other endocrine metabolic diseases such as kidney disease, hypopituitarism, Cushing syndrome and other diseases that affect bone metabolism were excluded;

[0021] ② Patients with other tumor diseases were excluded;

[0022] ③ Patients who already have osteoporosis and have started taking anti-osteoporosis drugs were excluded;

[0023] ④ Patients who used drugs that affect bone metabolism, such as calcitonin and bisphosphonates, were excluded;

[0024] ⑤ Patients who are currently pregnant or planning to become pregnant are excluded;

[0025] ⑥ Exclude patients who are unwilling to cooperate.

[0026] Preferably, the detailed process in step 2 includes the following steps:

[0027] 1. Grouping of research subjects

[0028] According to the inclusion and exclusion criteria, a total of 30 healthy subjects were included as the control group and 64 patients with differentiated thyroid cancer who underwent TSH suppression therapy after surgery were included as the disease group. Statistical analysis was performed according to the following groups:

[0029] 1. Describe the general information of the patients: The diseased group was divided into 3 groups according to the T value, including 24 patients with T ≥ -1, 23 patients with -2.5<T<-1, and 17 patients with T ≤ -2.5.

[0030] 2. Comparison of BMD between patients undergoing TSH suppression therapy after thyroid cancer surgery and healthy people: The disease group and the healthy control group were compared. There were 64 cases in the disease group, including 40 males and 24 females. There were 30 cases in the healthy control group, including 18 males and 12 females. The disease group and the control group were matched in age, gender and major concomitant diseases (such as diabetes) at a ratio of about 2:1.

[0031] 3. The fracture risks obtained by different FRAX calculation models in the diseased group were divided into three groups according to the T value, including 24 cases with T≥-1, 23 cases with -2.5<T<-1, and 17 cases with T≤-2.5.

[0032] (II) Methods for examining hip density

[0033] The hip bone density of all patients was measured using the American dual-energy X-ray absorptiometry (DXA, XR-600) introduced by our hospital, and the measurement personnel were specially trained technicians in our hospital.

[0034] Preferably, the detailed process in step 3 includes the following steps:

[0035] First, log in to the website https: / / www.sheffield.ac.uk / FRAX / tool, select the Chinese model, and enter relevant information as required (including age, gender, low body mass index (BMI) ≤ 19kg / m2, previous history of fragility fractures, parental hip fracture history, history of glucocorticoid treatment, smoking, excessive drinking, rheumatoid arthritis, etc.), and the hip bone density T value can be entered selectively. Click to calculate the 10-year prediction value of osteoporotic fractures in major sites (PMOF) and hip fracture prediction value (PHF). We used three methods to calculate the fracture risk of the postoperative population of differentiated thyroid cancer and generated three sets of data. First, the 10-year prediction value of major osteoporotic fractures (PMOF) and hip fracture prediction value (PHF) were obtained without entering BMD-T. Secondly, based on the above information, enter the T value to calculate the fracture risk PMOF (substitute BMD-T) and PHF (substitute BMD-T) of this population. For the third group of data, when entering basic information, the patient's age was added accordingly according to the TSH weighted scoring method we specified. The rest of the information was the same as the first group (BMD-T ​​was still not entered), expressed as PMOF (TSH scoring) and PHF (TSH scoring). The FRAX age item was weighted according to the TSH level, and three FRAX calculation models were simulated:

[0036] 1. When TSH≤0.1, the age increases by 10 years; when 0.1<TSH≤0.5, the age increases by 5 years; when 0.5<TSH≤2, the age increases by 2 years; when TSH>2, the age does not increase and the patient’s own age is recorded.

[0037] 2. When TSH is less than 0.008 (lower than the measurable value), the age value increases by 15 years; when 0.008≤TSH<0.1, the age increases by 10 years; when 0.1<TSH≤0.2, the age increases by 5 years; when 0.2<TSH≤0.3, the age increases by 4 years; when 0.3<TSH≤0.4, the age increases by 3 years; when 0.4<TSH≤0.5, the age increases by 2 years; when 0.5<TSH≤1, the age increases by 1 year; when TSH>1, the age does not increase, and the patient’s own age is recorded.

[0038] 3. When TSH is less than 0.008 (lower than the measurable value), the age increases by 20 years; when TSH is less than 0.1, the age increases by 15 years; when 0.1 is less than TSH≤0.2, the age increases by 10 years; when 0.2 is less than TSH≤0.3, the age increases by 8 years; when 0.3 is less than TSH≤0.4, the age increases by 6 years; when 0.4 is less than TSH≤0.5, the age increases by 4 years; when 0.5 is less than TSH≤2, the age increases by 2 years; when TSH is greater than 2, the age does not increase, and the patient's own age is recorded.

[0039] By comparing the sensitivity, specificity and area under the ROC curve (AUC) of various models in predicting the risk of major osteoporotic fractures and hip fractures, the optimal FRAX weighted scoring model was selected, and the area under the curve, sensitivity, specificity, Youden index, optimal cutoff value, positive predictive value and negative predictive value of this model in predicting the risk of major osteoporotic fractures and hip fractures were calculated.

[0040] A: The gold standard for diagnosing osteoporosis

[0041] The DXA examination results (T value) are used as the gold standard for diagnosing osteoporosis. According to the 2017 "Guidelines for the Diagnosis and Treatment of Primary Osteoporosis", the following definitions are used: T value ≥ -1.0 is normal; -2.5 < T value < -1.0 is low bone mass; T value ≤ -2.5 is osteoporosis; T value ≤ -2.5 + brittle fracture is severe osteoporosis.

[0042] B: Statistical analysis and processing

[0043] SPSS26.0 and MedCalc statistical software were used for analysis. Continuous variables that met normal distribution were analyzed by independent sample t test, those that did not meet normal distribution were analyzed by Mann-Whitney U test, and intergroup comparisons were performed by analysis of variance. Continuous variables that met normal distribution were expressed as mean ± standard deviation, and those that did not meet normal distribution were expressed as median and interquartile range [M(P25, P75)]. Categorical variables such as gender, smoking history, previous fracture history, and secondary osteoporosis were analyzed by X2 test or Fisher's exact test, expressed as frequency and percentage. Bone density T value ≤-2.5 was used as the gold standard for diagnosing osteoporosis, and the ROC curve of the FRAX model was drawn. The optimal cutoff value was determined by the Youden index. All statistical results were expressed as [95% confidence interval (CI)], and P < 0.05 was considered statistically significant.

[0044] Preferably, the detailed process in step 4 includes the following steps:

[0045] (I) Comparison of three weighted scoring FRAX models

[0046] For the prediction of osteoporosis, ROC curve analysis was used to determine the optimal cutoff value of the FRAX tool for predicting the risk of major osteoporotic fractures and hip fractures. The three simulated FRAX calculation models were compared, and the areas under the curve of PMOF scores 1, 2, and 3 were 0.722, 0.723, and 0.708, respectively; the sensitivities were 0.765, 0.588, and 0.412, respectively; and the specificities were 0.596, 0.83, and 0.936, respectively. The areas under the curve of PHF scores 1, 2, and 3 were 0.738, 0.744, and 0.72, respectively; the sensitivities were 0.471, 0.588, and 0.471, respectively; and the specificities were 0.872, 0.83, and 0.915, respectively. By comparing the specificity, sensitivity and area under the ROC curve of each model in predicting the risk of major osteoporotic fractures and hip fractures, the FRAX calculation model of scoring scheme 3 was finally selected as the FRAX weighted scoring model algorithm for this patient population, expressed as PMOF / PHF (TSH scoring)

[0047] (II) Comparison between the new weighted FRAX algorithm and the original FRAX algorithm

[0048] In PMOF / PHF, the area under the curve (AUC) values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.694 (95% CI = 32.5-54.8) and 0.683 (95% CI = 28.4-50.1), respectively. The optimal cutoff values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 2.15 and 0.25, respectively, at which the Youden index (sensitivity + specificity - 1) was the largest; the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.765 and 0.706, 0.638 and 0.596, 0.433 and 0.387, and 0.882 and 0.848, respectively. In PMOF / PHF (substituted with BMD-T), the AUC values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.976 (95% CI = 63.9-94.1) and 0.989 (95% CI = 65.5-94.4), respectively. The optimal cutoff values ​​were 4.15 and 1.1, respectively, when the Youden index was the largest; the sensitivity, specificity, PPV and NPV were 0.941 and 1, 0.936 and 0.936, 0.842 and 0.85, 0.978 and 1, respectively. In PMOF / PHF (TSH scoring), the AUC values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.708 (95% CI = 40.5-88.9) and 0.72 (95% CI = 40.8-85.3), respectively. The optimal cutoff values ​​were 5.5 and 1.55, respectively, when the Youden index was the largest, and the sensitivity, specificity, PPV, and NPV were 0.412 and 0.471, 0.936 and 0.915, 0.7 and 0.667, 0.815 and 0.827, respectively;

[0049] The 64 patients in the disease group were divided into three groups according to the T value. The fracture risk of the three groups was calculated by using the two original algorithms of FRAX and the FRAX weighted model finally selected in this study. Since the data were skewed when grouped according to the T value, the median and interquartile range [M(P25, P75)] were used. Among them, there were 24 cases with T≥-1, 23 cases with -2.5<T<-1, and 17 cases with T≤-2.5. After statistical analysis of the calculated fracture risk, it was found that the fracture risk of PMOF / PHF, PMOF / PHF (substituted into BMD-T), and PMOF / PHF (TSH score) were statistically significant among the fracture risk groups (P<0.05), and the fracture risk obtained increased with the decrease of T value.

[0050] Preferably, the detailed process in step six includes the following steps:

[0051] A: The FRAX tool is suitable for patients with differentiated thyroid cancer who have undergone TSH suppression therapy after surgery. Without substituting BMD-T, the FRAX tool has a certain value in predicting fracture risk for this patient population. This study uses a new FRAX model algorithm based on TSH levels after weighted scoring of age items, which can significantly improve the specificity of the FRAX tool in predicting fracture risk for this population, and early screening of patients with high fracture risk after TSH suppression therapy for thyroid cancer after surgery, so as to further carry out early intervention treatment.

[0052] B: We used bone density T value ≤-2.5 as the gold standard for diagnosing osteoporosis, simulated three FRAX models after TSH weighted scoring, and drew ROC curves. Through analysis and comparison, the specificity of the third FRAX model algorithm was the highest among the three groups. Considering that this patient population is a patient who has received TSH suppression therapy after thyroid cancer surgery, the target value of TSH suppression may gradually increase with the increase of disease course and the decrease of tumor recurrence risk, and the effect on bone density will also be weakened. Therefore, we chose the third FRAX weighted model algorithm with the highest specificity to identify patients with high risk of osteoporosis fractures at an early stage, so as to further intervene in the treatment at an early stage. By comparing the new FRAX model algorithm after weighted scoring based on TSH level with the two original FRAX algorithms through ROC curve comparison, it can be concluded that the specificity of PMOF / PHF (TSH scoring) diagnosis is close to PMOF / PHF (substituting BMD-T), which can improve the diagnostic efficacy of the new FRAX algorithm for osteoporosis. When the three types of fracture risks, PMOF / PHF, PMOF / PHF (substituting into BMD-T) and PMOF / PHF (TSH scoring) were grouped and tested according to T values, it was found that the fracture risk of the new algorithm after FRAX weighting was that the lower the bone density T value, the higher the fracture risk; the new algorithm after FRAX weighting had a higher value in predicting the fracture risk of this population.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] In the process of medical care evaluation of the present invention, all evaluation methods, evaluation of drug dosage and the like are based on certain criteria. The new FRAX algorithm that assigns points according to TSH levels is used to evaluate the risk of osteoporosis fractures in patients undergoing TSH suppression therapy after surgery for differentiated thyroid cancer, and optimize the fracture prediction value of the FRAX tool for this specific population, thereby greatly improving the evaluation accuracy of the subject and the range of the population covered by the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Comparison of ROC curves of PMOF for three weighted FRAX models;

[0056] Figure 2 Comparison of ROC curves of PHF for three weighted scoring FRAX models;

[0057] Figure 3 Comparison of ROC curves of PMOF between the new weighted FRAX algorithm and the original FRAX algorithm;

[0058] Figure 4 Comparison of ROC curves of PHF between the new weighted FRAX algorithm and the original FRAX algorithm. DETAILED DESCRIPTION

[0059] The method for assessing the risk of osteoporotic fractures after TSH suppression therapy after thyroid cancer surgery includes the following steps:

[0060] Step 1: Determine the research subjects and establish the inclusion and exclusion criteria of the evaluation method for the research subjects;

[0061] Step 2: Confirm the research method according to step 1 and refine it to the specific research and inspection method of specific parts;

[0062] Step 3: Establish the FRAX calculation and TSH weighted scoring method based on the results of the study in step 2;

[0063] Step 4: Carry out classification inspection and comparison based on the inspection results of step 3;

[0064] Step 5: Perform multiple rechecks and verifications based on the comparison results of step 4;

[0065] Step 6: Summarize the conclusions obtained from all the above steps.

[0066] The detailed process in step 1 includes the following steps:

[0067] A: A total of 64 patients with differentiated thyroid cancer who underwent thyroidectomy and took oral levothyroxine tablets for TSH suppression therapy in our hospital from October 2021 to May 2022, and 30 healthy people were collected. Among them, there were 40 males and 24 females in the diseased group. All patients were over 20 years old and had hip bone density measurements, all expressed as T values ​​(the T value was obtained according to the reference standard, that is, the World Health Organization standard T index provided by the NHANESⅢ database covering white women aged 20-29). During the consultation, the doctor conducted a questionnaire survey on the patients and collected the general information and medical history of the patients, mainly including gender, age, height, weight, operation time, history of fragility fracture, history of rheumatoid arthritis, previous history of chronic diseases (hypertension, diabetes, coronary heart disease, etc.), history of hip fracture of parents, smoking, drinking, history of hormone use, secondary osteoporosis, history of thyroid and parathyroid dysfunction, etc. This study was conducted with the informed consent of the included subjects and has been approved by the Research Ethics Committee of the 960th Hospital of the People's Liberation Army (approval number: (2022) Research Ethics No. (45));

[0068] B: Establishing inclusion and exclusion criteria for evaluation methods

[0069] 1. Inclusion criteria

[0070] ① Patients diagnosed with differentiated thyroid cancer who have undergone TSH suppression therapy for at least 6 months after thyroidectomy and have undergone hip bone density examination;

[0071] ② Aged 20 or above, with normal communication and comprehension abilities, able to carry out normal activities and adhere to follow-up;

[0072] ③After fully understanding and informed consent, voluntarily participate in this study and sign the informed consent form.

[0073] 2. Exclusion criteria

[0074] ① Patients with thyroid and parathyroid dysfunction, other endocrine metabolic diseases such as kidney disease, hypopituitarism, Cushing syndrome and other diseases that affect bone metabolism were excluded;

[0075] ② Patients with other tumor diseases were excluded;

[0076] ③ Patients who already have osteoporosis and have started taking anti-osteoporosis drugs were excluded;

[0077] ④ Patients who used drugs that affect bone metabolism, such as calcitonin and bisphosphonates, were excluded;

[0078] ⑤ Patients who are currently pregnant or planning to become pregnant are excluded;

[0079] ⑥ Exclude patients who are unwilling to cooperate.

[0080] The detailed process in step 2 includes the following steps:

[0081] 1. Grouping of research subjects

[0082] According to the inclusion and exclusion criteria, a total of 30 healthy subjects were included as the control group and 64 patients with differentiated thyroid cancer who underwent TSH suppression therapy after surgery were included as the disease group. Statistical analysis was performed according to the following groups:

[0083] 1. Describe the general information of the patients: The diseased group was divided into 3 groups according to the T value, including 24 patients with T ≥ -1, 23 patients with -2.5<T<-1, and 17 patients with T ≤ -2.5.

[0084] 2. Comparison of BMD between patients undergoing TSH suppression therapy after thyroid cancer surgery and healthy people: The disease group and the healthy control group were compared. There were 64 cases in the disease group, including 40 males and 24 females. There were 30 cases in the healthy control group, including 18 males and 12 females. The disease group and the control group were matched in age, gender and major concomitant diseases (such as diabetes) at a ratio of about 2:1.

[0085] 3. The fracture risks obtained by different FRAX calculation models in the diseased group were divided into three groups according to the T value, including 24 cases with T≥-1, 23 cases with -2.5<T<-1, and 17 cases with T≤-2.5.

[0086] (II) Methods for examining hip density

[0087] The hip bone density of all patients was measured using the American dual-energy X-ray absorptiometry (DXA, XR-600) introduced by our hospital, and the measurement personnel were specially trained technicians in our hospital.

[0088] The detailed process in step 3 includes the following steps:

[0089] First, log in to the website https: / / www.sheffield.ac.uk / FRAX / tool, select the Chinese model, and enter relevant information as required (including age, gender, low body mass index (BMI) ≤ 19kg / m2, previous history of fragility fractures, parental hip fracture history, history of glucocorticoid treatment, smoking, excessive drinking, rheumatoid arthritis, etc.), and the hip bone density T value can be entered selectively. Click to calculate the 10-year prediction value of osteoporotic fractures in major sites (PMOF) and hip fracture prediction value (PHF). We used three methods to calculate the fracture risk of the postoperative population of differentiated thyroid cancer and generated three sets of data. First, the 10-year prediction value of major osteoporotic fractures (PMOF) and hip fracture prediction value (PHF) were obtained without entering BMD-T. Secondly, based on the above information, enter the T value to calculate the fracture risk PMOF (substitute BMD-T) and PHF (substitute BMD-T) of this population. For the third group of data, when entering basic information, the patient's age was added accordingly according to the TSH weighted scoring method we specified. The rest of the information was the same as the first group (BMD-T ​​was still not entered), expressed as PMOF (TSH scoring) and PHF (TSH scoring). The FRAX age item was weighted according to the TSH level, and three FRAX calculation models were simulated:

[0090] 1. When TSH≤0.1, the age increases by 10 years; when 0.1<TSH≤0.5, the age increases by 5 years; when 0.5<TSH≤2, the age increases by 2 years; when TSH>2, the age does not increase and the patient’s own age is recorded.

[0091] 2. When TSH is less than 0.008 (lower than the measurable value), the age value increases by 15 years; when 0.008≤TSH<0.1, the age increases by 10 years; when 0.1<TSH≤0.2, the age increases by 5 years; when 0.2<TSH≤0.3, the age increases by 4 years; when 0.3<TSH≤0.4, the age increases by 3 years; when 0.4<TSH≤0.5, the age increases by 2 years; when 0.5<TSH≤1, the age increases by 1 year; when TSH>1, the age does not increase, and the patient’s own age is recorded.

[0092] 3. When TSH is less than 0.008 (lower than the measurable value), the age increases by 20 years; when TSH is less than 0.1, the age increases by 15 years; when 0.1 is less than TSH≤0.2, the age increases by 10 years; when 0.2 is less than TSH≤0.3, the age increases by 8 years; when 0.3 is less than TSH≤0.4, the age increases by 6 years; when 0.4 is less than TSH≤0.5, the age increases by 4 years; when 0.5 is less than TSH≤2, the age increases by 2 years; when TSH is greater than 2, the age does not increase, and the patient's own age is recorded.

[0093] By comparing the sensitivity, specificity and area under the ROC curve (AUC) of various models in predicting the risk of major osteoporotic fractures and hip fractures, the optimal FRAX weighted scoring model was selected, and the area under the curve, sensitivity, specificity, Youden index, optimal cutoff value, positive predictive value and negative predictive value of this model in predicting the risk of major osteoporotic fractures and hip fractures were calculated.

[0094] A: The gold standard for diagnosing osteoporosis

[0095] The DXA examination results (T value) are used as the gold standard for diagnosing osteoporosis. According to the 2017 "Guidelines for the Diagnosis and Treatment of Primary Osteoporosis", the following definitions are used: T value ≥ -1.0 is normal; -2.5 < T value < -1.0 is low bone mass; T value ≤ -2.5 is osteoporosis; T value ≤ -2.5 + brittle fracture is severe osteoporosis.

[0096] B: Statistical analysis and processing

[0097] SPSS26.0 and MedCalc statistical software were used for analysis. Continuous variables that met normal distribution were analyzed by independent sample t test, those that did not meet normal distribution were analyzed by Mann-Whitney U test, and intergroup comparisons were performed by analysis of variance. Continuous variables that met normal distribution were expressed as mean ± standard deviation, and those that did not meet normal distribution were expressed as median and interquartile range [M(P25, P75)]. Categorical variables such as gender, smoking history, previous fracture history, and secondary osteoporosis were analyzed by X2 test or Fisher's exact test, expressed as frequency and percentage. Bone density T value ≤-2.5 was used as the gold standard for diagnosing osteoporosis, and the ROC curve of the FRAX model was drawn. The optimal cutoff value was determined by the Youden index. All statistical results were expressed as [95% confidence interval (CI)], and P < 0.05 was considered statistically significant.

[0098] The detailed process in step 4 includes the following steps:

[0099] (I) Comparison of three weighted scoring FRAX models

[0100] For the prediction of osteoporosis, ROC curve analysis was used to determine the optimal cutoff value of the FRAX tool for predicting the risk of major osteoporotic fractures and hip fractures. The three simulated FRAX calculation models were compared, and the areas under the curve of PMOF scores 1, 2, and 3 were 0.722, 0.723, and 0.708, respectively; the sensitivities were 0.765, 0.588, and 0.412, respectively; and the specificities were 0.596, 0.83, and 0.936, respectively. The areas under the curve of PHF scores 1, 2, and 3 were 0.738, 0.744, and 0.72, respectively; the sensitivities were 0.471, 0.588, and 0.471, respectively; and the specificities were 0.872, 0.83, and 0.915, respectively. By comparing the specificity, sensitivity and area under the ROC curve of each model in predicting the risk of major osteoporotic fractures and hip fractures, the FRAX calculation model of scoring scheme 3 was finally selected as the FRAX weighted scoring model algorithm for this patient population, expressed as PMOF / PHF (TSH scoring). Figure 1 , Figure 2 , Table 3.

[0101] Table 3 Comparison of the predictive value of three weighted FRAX models

[0102]

[0103] (II) Comparison between the new weighted FRAX algorithm and the original FRAX algorithm

[0104] In PMOF / PHF, the area under the curve (AUC) values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.694 (95% CI = 32.5-54.8) and 0.683 (95% CI = 28.4-50.1), respectively. The optimal cutoff values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 2.15 and 0.25, respectively, at which the Youden index (sensitivity + specificity - 1) was the largest; the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.765 and 0.706, 0.638 and 0.596, 0.433 and 0.387, and 0.882 and 0.848, respectively. In PMOF / PHF (substituted with BMD-T), the AUC values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.976 (95% CI = 63.9-94.1) and 0.989 (95% CI = 65.5-94.4), respectively. The optimal cutoff values ​​were 4.15 and 1.1, respectively, when the Youden index was the largest; the sensitivity, specificity, PPV and NPV were 0.941 and 1, 0.936 and 0.936, 0.842 and 0.85, 0.978 and 1, respectively. In PMOF / PHF (TSH scoring), the AUC values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.708 (95% CI = 40.5-88.9) and 0.72 (95% CI = 40.8-85.3), respectively. The optimal cutoff values ​​were 5.5 and 1.55, respectively, when the Youden index was the largest, and the sensitivity, specificity, PPV and NPV were 0.412 and 0.471, 0.936 and 0.915, 0.7 and 0.667, 0.815 and 0.827, respectively.

[0105] Table 4 Comparison of the prediction value between the new weighted FRAX algorithm and the original FRAX algorithm

[0106]

[0107] The 64 patients in the disease group were divided into three groups according to the T value. The two original algorithms of FRAX and the FRAX weighted model finally selected in this study were used to calculate the fracture risk of the three groups. Since the data were skewed when grouped according to the T value, the median and interquartile range [M(P25, P75)] were used to express it. Among them, there were 24 cases with T≥-1, 23 cases with -2.5<T<-1, and 17 cases with T≤-2.5. After statistical analysis of the calculated fracture risk, it was found that the fracture risk of PMOF / PHF, PMOF / PHF (substituted into BMD-T), and PMOF / PHF (TSH score) were statistically significant among the fracture risk groups (P<0.05), and the fracture risk obtained increased with the decrease of T value. See Table 5.

[0108] Table 5 Comparison of fracture risk at different T-score levels

[0109]

[0110] The detailed process in step six includes the following steps:

[0111] A: The FRAX tool is suitable for patients with differentiated thyroid cancer who have undergone TSH suppression therapy after surgery. Without substituting BMD-T, the FRAX tool has a certain value in predicting fracture risk for this patient population. This study uses a new FRAX model algorithm based on TSH levels after weighted scoring of age items, which can significantly improve the specificity of the FRAX tool in predicting fracture risk for this population, and early screening of patients with high fracture risk after TSH suppression therapy for thyroid cancer after surgery, so as to further carry out early intervention treatment.

[0112] B: We used bone density T value ≤-2.5 as the gold standard for diagnosing osteoporosis, simulated three FRAX models after TSH weighted scoring, and drew ROC curves. Through analysis and comparison, the specificity of the third FRAX model algorithm was the highest among the three groups. Considering that this patient population is a patient who has received TSH suppression therapy after thyroid cancer surgery, the target value of TSH suppression may gradually increase with the increase of disease course and the decrease of tumor recurrence risk, and the effect on bone density will also be weakened. Therefore, we chose the third FRAX weighted model algorithm with the highest specificity to identify patients with high risk of osteoporosis fractures at an early stage, so as to further intervene in the treatment at an early stage. By comparing the new FRAX model algorithm after weighted scoring based on TSH level with the two original FRAX algorithms through ROC curve comparison, it can be concluded that the specificity of PMOF / PHF (TSH scoring) diagnosis is close to PMOF / PHF (substituting BMD-T), which can improve the diagnostic efficacy of the new FRAX algorithm for osteoporosis. When the three types of fracture risks, PMOF / PHF, PMOF / PHF (substituting into BMD-T) and PMOF / PHF (TSH scoring) were grouped and tested according to T values, it was found that the fracture risk of the new algorithm after FRAX weighting was that the lower the bone density T value, the higher the fracture risk; the new algorithm after FRAX weighting had a higher value in predicting the fracture risk of this population.

[0113] In summary: the method for evaluating the risk of osteoporotic fractures in patients with TSH suppression therapy after thyroid cancer surgery, all evaluation methods, evaluation of drug dosages and are based on certain, using the new FRAX algorithm that assigns points according to TSH levels to evaluate the risk of osteoporotic fractures in patients with differentiated thyroid cancer who undergo TSH suppression therapy after surgery, and optimize the fracture prediction value of the FRAX tool for this specific population, thereby greatly improving the accuracy of its main assessment and the range of population covered by the assessment.

Claims

1. A method for assessing the risk of osteoporotic fractures in patients undergoing TSH suppression therapy after thyroid cancer surgery, comprising the following steps: Step 1: Determine the research subjects and set up inclusion and exclusion criteria for the evaluation methods according to the research subjects; Step 2: Confirm the research method according to step 1 and refine the specific research and inspection methods for specific parts; Step 3: Establish the FRAX calculation model and the weighted scoring method based on TSH levels based on the research and examination results of step 2; Step 4: Carry out classification detection comparison and statistical analysis based on the research and inspection results of step 3; Step 5: Perform multiple rechecks and verifications based on the comparison results of step 4; Step 6: Summarize the conclusions obtained from all the above steps.

2. The method for evaluating the risk of osteoporotic fractures in patients undergoing TSH suppression therapy after thyroid cancer surgery according to claim 1, characterized in that The detailed process in step 1 includes the following steps: A: A total of 64 patients with differentiated thyroid cancer who underwent thyroidectomy and took oral levothyroxine tablets for TSH suppression therapy in our hospital from October 2021 to May 2022, and 30 healthy people were included. Among them, there were 40 males and 24 females in the diseased group. All patients were over 20 years old and had undergone hip bone density measurement, all expressed as T values ​​(the T value was obtained according to the reference standard, that is, it covered the World Health Organization standard T index provided by the NHANESⅢ database). During the consultation, the doctor conducted a questionnaire survey on the patients and collected the general information and medical history of the patients, mainly including gender, age, height, weight, operation time, history of fragility fracture, history of rheumatoid arthritis, previous chronic disease history (hypertension, diabetes, coronary heart disease, etc.), history of hip fracture of parents, smoking, drinking, history of hormone use, secondary osteoporosis, history of thyroid and parathyroid dysfunction, etc. This study was conducted with the informed consent of the included subjects and has been approved by the Scientific Research Ethics Committee of the 960th Hospital of the People's Liberation Army (Approval No.: (2022) Scientific Research Ethics No. (45)); B: Establishing inclusion and exclusion criteria for evaluation methods 1. Inclusion criteria ① Patients diagnosed with differentiated thyroid cancer who have undergone TSH suppression therapy for at least 6 months after thyroidectomy and have undergone hip bone density examination; ② Aged 20 or above, with normal communication and comprehension abilities, able to carry out normal activities and adhere to follow-up; ③After fully understanding and informed consent, voluntarily participate in this study and sign the informed consent form.

2. Exclusion criteria ① Patients with thyroid and parathyroid dysfunction, other endocrine metabolic diseases such as kidney disease, hypopituitarism, Cushing syndrome and other diseases that affect bone metabolism were excluded; ② Patients with other tumor diseases were excluded; ③ Patients who already have osteoporosis and have started taking anti-osteoporosis drugs were excluded; ④ Patients who used drugs that affect bone metabolism, such as calcitonin and bisphosphonates, were excluded; ⑤ Patients who are currently pregnant or planning to become pregnant are excluded; ⑥ Exclude patients who are unwilling to cooperate.

3. The method for evaluating the risk of osteoporotic fractures in patients undergoing TSH suppression therapy after thyroid cancer surgery according to claim 1, characterized in that The detailed process in step 2 includes the following steps:

1. Grouping of research subjects According to the inclusion and exclusion criteria, a total of 30 healthy subjects were included as the control group and 64 patients with differentiated thyroid cancer who underwent TSH suppression therapy after surgery were included as the disease group. Statistical analysis was performed according to the following groups:

1. Describe the general information of the patients: The diseased group was divided into 3 groups according to the T value, including 24 patients with T ≥ -1, 23 patients with -2.5<T<-1, and 17 patients with T ≤ -2.

5.

2. Comparison of BMD between patients undergoing TSH suppression therapy after thyroid cancer surgery and healthy people: The disease group and the healthy control group were compared. There were 64 cases in the disease group, including 40 males and 24 females. There were 30 cases in the healthy control group, including 18 males and 12 females. The age and gender ratios of the disease group and the healthy control group were matched at a ratio of about 2:

1.

3. The fracture risks obtained by different FRAX calculation models in the diseased group were divided into three groups according to the T value, including 24 cases with T≥-1, 23 cases with -2.5<T<-1, and 17 cases with T≤-2.

5. (II) Methods for examining hip density The hip bone density of all patients was measured using the American dual-energy X-ray absorptiometry (DXA, XR-600) introduced by our hospital, and the measurement personnel were specially trained technicians in our hospital.

4. The method for evaluating the risk of osteoporotic fractures in patients undergoing TSH suppression therapy after thyroid cancer surgery according to claim 1, characterized in that: The detailed process in step 3 includes the following steps: First, log in to the website https: / / www.sheffield.ac.uk / FRAX / tool, select the Chinese model, and enter relevant information as required (including age, gender, low body mass index (BMI) ≤ 19kg / m2, previous history of fragility fractures, parental hip fracture history, history of glucocorticoid treatment, smoking, excessive drinking, rheumatoid arthritis, etc.), and the hip bone density T value can be entered selectively. Click to calculate the 10-year prediction value of osteoporotic fractures in major sites (PMOF) and hip fracture prediction value (PHF). We used three methods to calculate the fracture risk of the postoperative population of differentiated thyroid cancer and generated three sets of data. First, the 10-year prediction value of major osteoporotic fractures (PMOF) and hip fracture prediction value (PHF) were obtained without entering BMD-T. Secondly, based on the above information, enter the T value to calculate the fracture risk PMOF (substitute BMD-T) and PHF (substitute BMD-T) of this population. For the third group of data, when entering basic information, the patient's age was added accordingly according to the TSH weighted scoring method we specified. The rest of the information was the same as the first group (BMD-T ​​was still not entered), expressed as PMOF (TSH scoring) and PHF (TSH scoring). The FRAX age item was weighted according to the TSH level, and three FRAX calculation models were simulated: Model 1: When TSH≤0.1, the age item is increased by 10 years; when 0.1<TSH≤0.5, the age item is increased by 5 years; when 0.5<TSH≤2, the age item is increased by 2 years; when TSH>2, the age item is not increased, and the patient's own age is recorded. Model 2: When TSH is less than 0.008 (lower than the measurable value), the age item value increases by 15 years; when 0.008≤TSH<0.1, the age item increases by 10 years; when 0.1<TSH≤0.2, the age item increases by 5 years; when 0.2<TSH≤0.3, the age item increases by 4 years; when 0.3<TSH≤0.4, the age item increases by 3 years; when 0.4<TSH≤0.5, the age item increases by 2 years; when 0.5<TSH≤1, the age item increases by 1 year; when TSH>1, the age item value does not increase, and the patient's own age is entered. Model 3: When TSH is less than 0.008 (lower than the measurable value), the age item increases by 20 years; when TSH is less than 0.1, the age item increases by 15 years; when 0.1 is less than TSH≤0.2, the age item increases by 10 years; when 0.2 is less than TSH≤0.3, the age item increases by 8 years; when 0.3 is less than TSH≤0.4, the age item increases by 6 years; when 0.4 is less than TSH≤0.5, the age item increases by 4 years; when 0.5 is less than TSH≤2, the age item increases by 2 years; when TSH is greater than 2, the age item value does not increase, and the patient's own age is entered. By comparing the sensitivity, specificity and area under the ROC curve (AUC) of various models in predicting the risk of major osteoporotic fractures and hip fractures, the optimal FRAX weighted scoring model was selected, and the area under the curve, sensitivity, specificity, Youden index, optimal cutoff value, positive predictive value and negative predictive value of this model in predicting the risk of major osteoporotic fractures and hip fractures were calculated. A: The gold standard for diagnosing osteoporosis The DXA examination results (T value) are used as the gold standard for diagnosing osteoporosis. According to the 2017 "Guidelines for the Diagnosis and Treatment of Primary Osteoporosis", the following definitions are used: T value ≥ -1.0 is normal; -2.5 < T value < -1.0 is low bone mass; T value ≤ -2.5 is osteoporosis; T value ≤ -2.5 + brittle fracture is severe osteoporosis. B: Statistical analysis and processing SPSS26.0 and MedCalc statistical software were used for analysis. Continuous variables that met normal distribution were analyzed by independent sample t test, those that did not meet normal distribution were analyzed by Mann-Whitney U test, and intergroup comparisons were performed by analysis of variance. Continuous variables that met normal distribution were expressed as mean ± standard deviation, and those that did not meet normal distribution were expressed as median and interquartile range [M(P25, P75)]. Categorical variables such as gender, smoking history, previous fracture history, and secondary osteoporosis were analyzed by X2 test or Fisher's exact test, expressed as frequency and percentage. Bone density T value ≤-2.5 was used as the gold standard for diagnosing osteoporosis, and the ROC curve of the FRAX model was drawn. The optimal cutoff value was determined by the Youden index. All statistical results were expressed as [95% confidence interval (CI)], and P < 0.05 was considered statistically significant.

5. The method for evaluating the risk of osteoporotic fractures in TSH suppression therapy after thyroid cancer surgery according to claim 1, characterized in that The detailed process in step 4 includes the following steps: (I) Comparison of three weighted scoring FRAX models For the prediction of osteoporosis, ROC curve analysis was used to determine the optimal cutoff value of the FRAX tool for predicting the risk of major osteoporotic fractures and hip fractures. The three simulated FRAX calculation models were compared, and the areas under the curve of PMOF scores 1, 2, and 3 were 0.722, 0.723, and 0.708, respectively; the sensitivities were 0.765, 0.588, and 0.412, respectively; and the specificities were 0.596, 0.83, and 0.936, respectively. The areas under the curve of PHF scores 1, 2, and 3 were 0.738, 0.744, and 0.72, respectively; the sensitivities were 0.471, 0.588, and 0.471, respectively; and the specificities were 0.872, 0.83, and 0.915, respectively. By comparing the specificity, sensitivity and area under the ROC curve of each model in predicting the risk of major osteoporotic fractures and hip fractures, the FRAX calculation model of scoring scheme 3 was finally selected as the FRAX weighted scoring model algorithm for this patient population, expressed as PMOF / PHF (TSH scoring). (II) Comparison between the new weighted FRAX algorithm and the original FRAX algorithm In PMOF / PHF, the area under the curve (AUC) values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.694 (95% CI = 32.5-54.8) and 0.683 (95% CI = 28.4-50.1), respectively. The optimal cutoff values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 2.15 and 0.25, respectively, at which the Youden index (sensitivity + specificity - 1) was the largest; the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.765 and 0.706, 0.638 and 0.596, 0.433 and 0.387, and 0.882 and 0.848, respectively. In PMOF / PHF (substituted with BMD-T), the AUC values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.976 (95% CI = 63.9-94.1) and 0.989 (95% CI = 65.5-94.4), respectively. The optimal cutoff values ​​were 4.15 and 1.1, respectively, when the Youden index was the largest; the sensitivity, specificity, PPV and NPV were 0.941 and 1, 0.936 and 0.936, 0.842 and 0.85, 0.978 and 1, respectively. In PMOF / PHF (TSH scoring), the AUC values ​​for predicting the risk of major osteoporotic fractures and hip fractures were 0.708 (95% CI = 40.5-88.9) and 0.72 (95% CI = 40.8-85.3), respectively. The optimal cutoff values ​​were 5.5 and 1.55, respectively, when the Youden index was the largest, and the sensitivity, specificity, PPV and NPV were 0.412 and 0.471, 0.936 and 0.915, 0.7 and 0.667, 0.815 and 0.827, respectively. The 64 patients in the disease group were divided into three groups according to the T value. The fracture risk of the three groups was calculated by using the two original algorithms of FRAX and the FRAX weighted model finally selected in this study. Since the data were skewed when grouped according to the T value, the median and interquartile range [M(P25, P75)] were used. Among them, there were 24 cases with T≥-1, 23 cases with -2.5<T<-1, and 17 cases with T≤-2.

5. After statistical analysis of the calculated fracture risk, it was found that the fracture risk of PMOF / PHF, PMOF / PHF (substituted into BMD-T), and PMOF / PHF (TSH score) were statistically significant among the fracture risk groups (P<0.05), and the fracture risk obtained increased with the decrease of T value.

6. The method for evaluating the risk of osteoporotic fractures in TSH suppression therapy after thyroid cancer surgery according to claim 1, characterized in that: The detailed process in step six includes the following conclusions: A: The FRAX tool is suitable for patients with differentiated thyroid cancer who have undergone TSH suppression therapy after surgery. Without substituting BMD-T, the FRAX tool has a certain value in predicting fracture risk for this patient population. This study uses a new FRAX model algorithm based on TSH levels after weighted scoring of age items, which can significantly improve the specificity of the FRAX tool in predicting fracture risk for this population, and early screening of patients with high fracture risk after TSH suppression therapy for thyroid cancer after surgery, so as to further carry out early intervention treatment. B: We used bone density T value ≤ -2.5 as the gold standard for diagnosing osteoporosis, simulated three FRAX models after TSH weighted scoring to draw ROC curves, and through analysis and comparison, the specificity of the third FRAX model algorithm was the highest among the three groups. Considering that this patient population is a patient undergoing TSH suppression therapy after thyroid cancer surgery, the target value of TSH suppression may gradually increase with the increase of disease course and the decrease of tumor recurrence risk, and the effect on bone density will also be weakened, so we chose the third FRAX weighted model algorithm with the highest specificity to identify patients with high osteoporosis fracture risk at an early stage, so as to further intervene in the treatment at an early stage. By comparing the new FRAX model algorithm with the original two FRAX algorithms after weighted scoring based on TSH level through ROC curve, it can be concluded that the specificity of PMOF / PHF (TSH scoring) diagnosis is close to PMOF / PHF (substituting BMD-T), which can improve the diagnostic efficiency of the new FRAX algorithm for osteoporosis. When the three fracture risks of PMOF / PHF, PMOF / PHF (substituting BMD-T), and PMOF / PHF (TSH scoring) were grouped and tested according to T values, it was found that the fracture risk of the new FRAX weighted algorithm was higher when the bone density T value was lower; the new FRAX weighted algorithm had a higher value in predicting the fracture risk of this population.

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