Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To explore the clinical efficacy and safety of one-stage posterior lesion removal and internal spinal fixation in patients with lumbar Brucellosis spondylitis.Methods The clinical data of 24 patients admitted from October 2017 to October 2022 were retrospectively analyzed,2 patients were lost to follow-up at 10 months after surgery,at the final 22 cases were included in the study,including 13 males and 9 females with an average age of(52.00±6.89)years old,were treated with one-stage posterior lesion removal and internal spinal fixation.The operation time,intraoperative bleeding,follow-up time,ery-throcyte sedimentation rate(ESR)and C-reactive protein(CRP)before and after operation were recorded.The pain visual ana-logue scale(VAS),Oswestry disability index(ODI),the Japanese Orthopaedic Association(JOA)score for neurofunction,American Spinal Injury Association(ASIA)spinal cord injury grade and modified MacNab criteria were ussed to evaluate the efficacy.Results All patients were followed up from 12 to 30 months with an average of(17.41±4.45)months.The operation time was 70 to 155 min with an average of(1 16.59±24.32)min;the intraoperative bleeding volume was 120 to 520 ml with an average of(275.00±97.53)ml.CRP and ESR levels decreased more significantly at 1 week and at the final follow-up than pre-operative levels(P＜0.05).VAS,JOA score and ODI at 1 week and at the latest follow-up were more significantly improved than preoperative results(P＜0.05).There was no significant difference between ASIA preoperative and 1 week after operation(P＞0.05),and a significant difference between preoperative and last follow-up(P＜0.05).In the final follow-up,21 patients had ex-cellent efficacy,1 patient had fair,and there was no recurrence during the follow-up.Conclusion One-stage transpedicular le-sion removal and internal spinal fixation,with few incisions and short operation time,helps the recovery of neurological func-tion,and the prognosis meets the clinical requirements,which can effectively control Brucella spondylitis.

Objective:To analyze the effects of different dose calculation grid size of Monaco system on the physical and biological dosimetry of target area and organ at risk (OAR) in T 4 nasopharyngeal carcinoma. Methods:A total of 18 patients with stage T 4 nasopharyngeal carcinoma who received radiotherapy in the Department of Radiotherapy of Yunnan Cancer Hospital from October 2020 to April 2022 were selected to complete the delineation of target areas and OAR in the Monaco 5.11.03 system, and the volumetric intensity modulated arc therapy (VMAT) plan was developed on the 3 mm grid with the optimization mode of target area priority. The 3 mm grid group plan was replicated without changing any other parameters, and the physical plan was re-established on the 1, 2, 4 and 5 mm grids, and then the five plans were normalized to the prescription dose to cover 95% of the target volume. The planning time, D 2%, D 50%, D 98%, conformity index (CI), homogeneity index (HI), gradient index (GI), tumor control probability (TCP), D 2% and D mean of important OAR around the target area were calculated and statistically analyzed. Results:Planning primary tumor gross target volume (PGTVp) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (76.94±0.66), (75.98±0.76), (75.56±0.67), (75.67±0.73) and (75.94±0.85) Gy, respectively, with a statistically significant difference ( F=9.86, P<0.001). The CI of 1, 2, 3, 4 and 5 mm groups were 0.75±0.05, 0.78±0.04, 0.78±0.05, 0.79±0.04 and 0.78±0.04, respectively, with a statistically significant difference ( F=2.61, P=0.041). There were statistically significant differences in D 50%, D 98%, HI, equivalent uniform dose (EUD) and tumor control probability (TCP) among the groups ( H=17.14, P=0.002; F=9.35, P<0.001; H=25.43, P<0.001; F=5.85, P<0.001; H=17.65, P=0.001). There was no statistically significant difference in GI among the groups ( P>0.05). Pairwise comparison showed that D 2% in 2, 3, 4, 5 mm groups compared with 1 mm group, D 50% in 5 mm group compared with 2, 3 mm groups, D 98% in 4 mm group compared with 1, 2 mm groups, D 98% in 5 mm group compared with 1, 2, 3 mm groups, CI in 5 mm group compared with 1 mm group, HI in 2, 3, 4, 5 mm groups compared with 1 mm group, EUD in 3 mm group was compared with 1 mm group, EUD in 5 mm group compared with 2, 3 mm groups, TCP in 3 mm group compared with 1 mm group, and TCP in 5 mm group compared with 3 mm group, there were statistically significant differences (all P<0.05). Planning nodal gross target volume (PGTVn) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (76.36±0.59), (75.36±0.62), (75.04±0.68), (75.25±0.72) and (75.39±0.77) Gy, respectively, with a statistically significant difference ( F=10.32, P<0.001). The HI of 1, 2, 3, 4 and 5 mm groups were 1.08 (1.08, 1.08), 1.07 (1.06, 1.07), 1.06 (1.06, 1.07), 1.06 (1.06, 1.07), 1.06 (1.06, 1.07), 1.06 (1.06, 1.08), respectively, with a statistically significant difference ( H=22.00, P<0.001) ; There were statistically significant differences in D 50%, D 98% and EUD among the groups ( H=11.79, P=0.019; H=20.49, P<0.001; F=12.14, P=0.016). Pairwise comparison showed that there were statistically significant differences in D 2% between 2, 3, 4, 5 mm groups and 1 mm group, D 98% between 4 mm group and 1 mm group, D 98% between 5 mm group and 1, 2 mm groups, HI between 2, 3, 4 mm groups and 1 mm group, and EUD between 3 mm group and 1 mm group (all P<0.05). Planning primary tumor clinical target volume 1 (PCTVp1) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (76.59±0.63), (75.64±0.65), (75.64±0.98), (75.41±0.70) and (75.71±0.84) Gy, respectively, with a statistically significant difference ( F=9.53, P<0.001). The D 50% of 1, 2, 3, 4, 5 mm groups were (72.09±0.34), (71.85±0.39), (71.82±0.45), (72.04±0.56), (72.43±0.66) Gy, respectively, with a statistically significant difference ( F=4.20, P=0.019). There was no statistically significant difference in the other indexes among the groups (all P>0.05). Pairwise comparison showed that there were statistically significant differences in D 2% between 2, 3, 4, 5 mm groups and 1 mm group, and in D 50% between 2, 3 mm groups and 1 mm group (all P<0.05). Planning nodal clinical target volume 1 (PCTVn1) : There were no statistically significant differences in all indexes among the groups (all P>0.05). Planning clinical target volume 2 (PCTV2) : The D 2% of 1, 2, 3, 4 and 5 mm groups were (75.57±0.50), (74.87±0.67), (74.51±0.51), (74.61±0.63) and (75.00±0.74) Gy, respectively, with a statistically significant difference ( F=8.27, P<0.001). Pairwise comparison showed that the D 2% of the 2, 3, 4 mm groups were significantly different from that of the 1 mm group (all P<0.05). The calculation time of physical plan in 1, 2, 4 and 5 mm groups was 987.00 (848.00, 1 091.00), 120.50 (99.75, 134.00), 26.00 (24.00, 34.25) and 21.50 (18.75, 34.75) s, respectively, with a statistically significant difference ( H=61.62, P<0.001). Pairwise comparison showed that there were statistically significant differences in the calculation time between 4 mm group and 1, 2 mm groups, 5 mm group and 1, 2 mm groups (all P<0.05). There was no statistically significant difference in the dosimetric parameters of OAR around the target area among the groups (all P>0.05) . Conclusion:The physical dose and biological dose of the important OAR around the target area and the target area change with the change of dose calculation grid size when formulating the physical plan of radiotherapy for T 4 nasopharyngeal carcinoma. Considering the quality of the physical plan and the calculation time, when the Monaco system formulates the VMAT plan for T 4 nasopharyngeal carcinoma patients, the plan can be optimized on the 3 mm computing grid and copied to the 1 mm computing grid for recalculation.

OBJECTIVE: To analyze the clinical effect of decompression and bone grafting on osteonecrosis of the femoral head(ONFH) at different sites of necrotic lesions. METHODS: A total of 105 patients with ARCOⅡstage ONFH admitted from January 2017 to December 2018 were retrospectively analyzed. There were 71 males and 34 females, with an average age of (55.20±10.98) years old. The mean course of all patients was(15.91±9.85) months. According to Japanese Inveatigation Committee (JIC) classification, all patients were divided into 4 types:17 cases of type A, 26 cases of type B, 33 cases of type C1 and 29 cases of type C2. All four groups were treated with decompression of the pulp core and bone grafting. Visual analogue scale(VAS) and Harris hip joint score were used before and at 3, 6, 12, and 24 months after the operation, and the collapse of the femoral head was observed by X-ray examination within 2 years. RESULTS: All 105 patients were successful on operation without complications, and the mean follow-up duration was (24.45±2.75) months. Harris score showed that there was no statistical difference among four groups before surgery and 3, 6 months after surgery (P>0.05);at 12 and 24 months after surgery, there were significant differences among all groups (P<0.01). There were significant differences in intragroup Harris scores at preoperative and postoperative time points among four groups (P<0.01). VAS showed that there was no statistical difference among four groups before and 3, 6 months after surgery (P>0.05);at 12 and 24 months after surgery, there were significant differences among all groups (P<0.01). There were significant differences in VAS at preoperative and postoperative time points among four groups (P<0.01). None of the patients in four groups had femoral head collapse before and 3, 6 months after surgery. At 12 months after operation, there were 3 cases of femoral head collapse in group C and 4 cases in group C2(P>0.05);At 24 months after operation, 1 case of femoral head collapse occurred in group B, 6 cases in group C1 and 8 cases in group C2(P<0.05). CONCLUSION Core decompression and bone grafting can improve the effect of ONFH and hip preservation. The effect of hip preservation for ONFH is closely related to the location of the osteonecrosis lesion, so the influence of the location of lesion on the effect of hip preservation should be considered in clinical treatment, so as to make better preoperative hip preservation plan.
Male ; Female ; Humans ; Adult ; Middle Aged ; Aged ; Retrospective Studies ; Femur Head Necrosis/diagnosis* ; Femur Head/surgery* ; Treatment Outcome ; Decompression, Surgical ; Bone Transplantation

Child ; Humans ; East Asian People ; Quality of Life ; Students ; Child Abuse, Sexual ; Young Adult ; Resilience, Psychological