Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population.

Artificial Intelligence (AI) models for medical diagnosis often face challenges of generalizability and fairness. We highlighted the algorithmic unfairness in a large thyroid ultrasound dataset with significant diagnostic performance disparities across subgroups linked causally to sample size imbalances. To address this, we introduced the Quasi-Pareto Improvement (QPI) approach and a deep learning implementation (QP-Net) combining multi-task learning and domain adaptation to improve model performance among disadvantaged subgroups without compromising overall population performance. On the thyroid ultrasound dataset, our method significantly mitigated the area under curve (AUC) disparity for three less-prevalent subgroups by 0.213, 0.112, and 0.173 while maintaining the AUC for dominant subgroups; we also further confirmed the generalizability of our approach on two public datasets: the ISIC2019 skin disease dataset and the CheXpert chest radiograph dataset. Here we show the QPI approach to be widely applicable in promoting AI for equitable healthcare outcomes.

Fecal Immunochemical Testing and the Risk of Advanced Colorectal Neoplasia: A Difference-In-Difference Analysis.

PURPOSE: To evaluate the effectiveness of fecal immunochemical testing (FIT) in colorectal cancer screening. METHODS: We conducted a prospective cohort study among 5,598 participants age 40-74 years between 2012 and 2020 in Tianjin, China. Inverse probability weighting was adopted to adjust for potential imbalanced factors between groups. A Cox proportional hazards model was used to estimate the weighted associations between FIT screening and advanced colorectal neoplasia. A difference-in-difference (DID) model was adopted to compare the incidence rates of advanced colorectal neoplasia between groups. RESULTS: In DID analysis, the rate of incidence was reduced by 0.34 cases per person-years in the screening group as compared with the historical FIT screening group (rate ratio [RR], 0.08 [95% CI, 0.07 to 0.10]) and by 0.06 cases per person-years in the non-FIT screening group as compared with the historical non-FIT screening group (RR, 0.37 [95% CI, 0.29 to 0.48]; P < .001 for both comparisons), with a relative reduction of 0.28. Similar benefit effect from FIT screening was observed in sex and age subgroups. CONCLUSION: FIT screening was associated with a reduction in incidence density from advanced colorectal neoplasia.

Association between blood heavy metals and lung cancer risk: A case-control study in China.

BACKGROUND: Exposure to various metals has been reported to lead to lung cancer. However, few studies focused on the combined effects of metal mixture. OBJECTIVE: To explore the relationship between metal mixture and lung cancer patients. METHODS: Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure the concentration of 8 heavy metals (V, Cr, Mn, Se, Mo, Cd, Ba and Pb) in serum samples of 86 cases and 105 controls in the Tianjin Lung Cancer Cohort. Logistic regression models were used to estimate the effect of each metal on the risk of lung cancer. The restricted cubic spline function was applied to describe the dose-response relationship between various metal concentrations and lung cancer risk. Bayesian Kernel Machine Regression (BKMR), Weighted Quantile Sum (WQS) and Quantile G-Computation (QGC) were employed to explore the effects of metal mixtures as a whole on lung cancer. RESULTS: An increased risk of lung cancer was associated with higher blood Mo concentration (adjusted OR = 2.94, 95% CI = 1.03-8.74 for tertile 2 vs. tertile 1). Higher Se concentration in blood may have protective effects on the risk of lung cancer (adjusted OR = 0.18, 95% CI = 0.06-0.51 for tertile 3 vs. tertile 1, p-trend <0.001). In addition, Se and Cd may have an antagonism effect on the occurrence of lung cancer (RERI and 95% CI = -0.95 [-31.77, -0.07]; AP and 95% CI = -0.95 [-5.16 -0.74]). Although the metal mixture did not show a significant effect on lung cancer as a whole, this may be due to the offsetting effect between positive and negative effects. CONCLUSIONS: Our research indicates that Se has a promising anti-cancer application, but it is necessary to prevent the role of Cd that antagonize Se in lung cancer.

Association of statin use and increase in lipoprotein(a): a real-world database research.

BACKGROUND: There is an increased concern that statins may have an unintended effect of elevated lipoprotein(a) [Lp(a)]. We conducted a large sample real-world study to test the association. METHODS: This retrospective cohort study was conducted using data from an integrated SuValue database, which includes 221 hospitals across China covering more than 200,000 of population with longitudinal follow-up to 10 years. Propensity score matching was applied to identify two comparable cohorts with statin users and non-statin users. Detailed follow-up information such as Lp(a) levels were extracted. The hazard ratio was calculated on Lp(a) changes based on the statin usage cohorts. Detailed subgroup and different characteristic cohorts' analyses were also conducted. RESULTS: After baseline propensity score matching, a total of 42,166 patients were included in a 1:1 matched ratio between statin users and non-statin users. In the case of no difference in low density lipoprotein (LDL-C), Lp(a) was increased significantly with the use of statins (adjusted HR 1.47; 95% confidence interval [CI] 1.43-1.50). Lp(a) increase was observed in various subgroup analyses and different cohorts. The dose intensity of statin was positively associated with the evaluated Lp(a) level. CONCLUSION: The use of statins was associated with an increased risk of Lp(a) elevation compared with non-statin use counterparts. The clinical relevance of these increases needs to be addressed in surrogate marker trials and/or large, cardiovascular outcomes trials.

Association between use of antihypertensive drugs and the risk of cancer: a population-based cohort study in Shanghai.

BACKGROUND: Previously studies shown a potential risk of antihypertensive medicines in relation to cancer susceptibility, which creating significant debate in the scientific community and public concern. We sought to investigate the relationship between antihypertensive medicines and cancer risk, by drug type and class. METHODS: We conducted a population-based cohort study and enrolled patients diagnosed with hypertension from community healthcare centers in Changning District, Shanghai, China. Antihypertensive drug administration were classified as five common antihypertensive drugs. The main outcomes were incidence of total cancer and by major cancer type. RESULTS: Between January 2013 and December 2017, a total of 101,370 hypertensive patients were enrolled in this cohort. During a mean follow-up of 5.1 (SD 1.3) years, 4970 cancer cases were newly diagnosed in the cohort. CCBs were the most frequently used antihypertensives which were associated with a moderately increased risk of total cancer (hazard ratio, HR = 1.11, 95% CI: 1.05-1.18). The second commonly used drug ARBs were also associated with increased risk of total cancer (HR = 1.10, 95%CI: 1.03-1.17) as well as lung and thyroid cancers (HR = 1.21, 95%CI: 1.05-1.39; HR = 1.62 95%CI: 1.18-2.21, respectively). No significant association was found between cancer and other antihypertensives. Hypertensive patients who use more than one class of antihypertensives drugs had a higher risk of total cancer (HR: 1.22, 95%CI: 1.10-1.35 for two classes; HR: 1.22, 95%CI: 1.03-1.45 for three or more classes), and a possible dose-response relationship was suggested (P for trend < 0.001). The risk of thyroid cancer was higher in hypertensive patients prescribed with three or more antihypertensive classes. CONCLUSIONS: Use of ARBs or CCBs may be associated with an increased risk of total cancer. Taking more than one class of antihypertensives drugs appeared to have a higher risk for total cancer.

In-hospital waiting time to surgery and functional outcomes in geriatric hip fractures: a directed acyclic graph-based preplanned analysis from a prospective multicenter cohort study.

BACKGROUND: The early recovery of hip function after hip fracture surgery values more attention, especially for patients with delayed surgery of longer than 48 h. We aim to evaluate the associations of in-hospital surgical waiting time with the functional outcomes [Harris Hip Score (HHS), Parker Mobility Score (PMS), and EuroQol 5 dimensions VAS (visual analogue scale) score (EQ-5D VAS)] in elderly patients who sustained hip fractures. MATERIALS AND METHODS: Data on sociodemographic and clinical factors were prospectively collected using a multicenter hip fracture registry system. Participants in the cohort underwent a 12-month follow-up investigation. After adjusting potential confounders identified by the directed acyclic graphs, the associations between surgical waiting time longer than 48 h and functional outcomes were estimated by log-binomial regression and multivariable linear regression models with generalized estimating equations. RESULTS: Of 863 survival participants with available functional data at 12 months after surgery, an increased risk was obtained from receiving surgery after 48 h and the poor functional outcomes (HHS<80: relative risk (RR)=1.56, 95% CI: 1.00-2.51; PMS<7: RR=1.49, 95% CI: 1.13-2.01; EQ-5D VAS<80: RR=1.97, 95% CI: 1.57-2.47). In-hospital waiting time greater than 48 h were time-invariantly associated with lower PMS during recovery (-0.44 units 95% CI: -0.70 to -0.18). In addition, delayed surgery was time-varying associated with HHS and EQ-5D VAS. CONCLUSIONS: The associations between in-hospital waiting time and postoperative functional score suggest that delayed surgery can lead to poor functional outcomes, especially in patients waiting longer than 72 h from injury. Delayed surgery mainly impacted hip function and mobility recovery with a slower speed in early recovery of the first 3 months. More attention should be paid to mechanisms behind the associations between delayed surgery on general healthy status.

Multi-omics profiling of papillary thyroid microcarcinoma reveals different somatic mutations and a unique transcriptomic signature.

BACKGROUND: Papillary thyroid microcarcinoma (PTMC) incidence has significantly increased, and some cases still exhibit invasive traits. The entire molecular landscape of PTMC, which can offer hints for the etiology of cancer, is currently absent. METHODS: We compared our findings with those for PTMC in the TCGA by analyzing the largest study at the current stage of whole exome sequencing and RNA-sequencing data from 64 patients with PTMC. Then, we systematically demonstrated the differences between the two PTMC subtypes based on multi-omics analyses. Additionally, we created a molecular prediction model for the PTMC subtypes and validated them among TCGA patients for individualized integrative assessment. RESULTS: In addition to the presence of BRAF mutations and RET fusions in the TCGA cohort, we also discovered a new molecular signature named PTMC-inflammatory that implies a potential response to immune intervention, which is enriched with AFP mutations, IGH@-ext fusions, elevated immune-related genes, positive peroxidase antibody, and positive thyroglobulin antibody. Additionally, a molecular prediction model for the PTMC-inflammatory patients was created and validated among TCGA patients, while the prognosis for these patients is poor. CONCLUSIONS: Our findings comprehensively define the clinical and molecular features of PTMC and may inspire new therapeutic hypotheses.

Integrated gene profiling of fine-needle aspiration sample improves lymph node metastasis risk stratification for thyroid cancer.

BACKGROUND: Lymph node metastasis risk stratification is crucial for the surgical decision-making of thyroid cancer. This study investigated whether the integrated gene profiling (combining expression, SNV, fusion) of Fine-Needle Aspiration (FNA) samples can improve the prediction of lymph node metastasis in patients with papillary thyroid cancer. METHODS: In this retrospective cohort study, patients with papillary thyroid cancer who went through thyroidectomy and central lymph node dissection were included. Multi-omics data of FNA samples were assessed by an integrated array. To predict lymph node metastasis, we built models using gene expressions or mutations (SNV and fusion) only and an Integrated Risk Stratification (IRS) model combining genetic and clinical information. Blinded histopathology served as the reference standard. ROC curve and decision curve analysis was applied to evaluate the predictive models. RESULTS: One hundred and thirty two patients with pathologically confirmed papillary thyroid cancer were included between 2016-2017. The IRS model demonstrated greater performance [AUC = 0.87 (0.80-0.94)] than either expression classifier [AUC = 0.67 (0.61-0.74)], mutation classifier [AUC = 0.61 (0.55-0.67)] or TIRADS score [AUC = 0.68 (0.62-0.74)] with statistical significance (p < 0.001), and the IRS model had similar predictive performance in large nodule [>1 cm, AUC = 0.88 (0.79-0.97)] and small nodule [≤1 cm, AUC = 0.84 (0.74-0.93)] subgroups. The genetic risk factor showed independent predictive value (OR = 10.3, 95% CI:1.1-105.3) of lymph node metastasis in addition to the preoperative clinical information, including TIRADS grade, age, and nodule size. CONCLUSION: The integrated gene profiling of FNA samples and the IRS model developed by the machine-learning method significantly improve the risk stratification of thyroid cancer, thus helping make wise decisions and reducing unnecessary extensive surgeries.

D-Limonene inhibits the occurrence and progression of LUAD through suppressing lipid droplet accumulation induced by PM2.5 exposure in vivo and in vitro.

BACKGROUND: PM2.5 exposure is associated with lung adenocarcinoma (LUAD), but the mechanism is unclear. The lack of understanding impedes our effort on prevention. This study examined a possible mechanism of lung cancer caused by PM2.5 exposure, and aimed to find a potential intervention for people living in PM2.5 polluted regions. METHODS: Electron microscopy and oil-red staining were conducted to examine the lipid droplet accumulation. Masson's trichrome staining, colony forming, scratch assay and transwell experiment were conducted to evaluate the effect of PM2.5 exposure and D-limonene intervention on the occurrence and progression of LUAD. Potential intervention targets were found by RNA-Seq and verified by luciferase reporter assay. MiR-195 KO mice constructed with CRISPR/Cas9 technology were used to investigate the pivotal role of D-limonene-miR-195-SREBP1/FASN axis. Cohort analysis of lung cancer patients, human LUAD tissues staining and human intervention trial were also conducted to validate the results of cell and animal experiments. RESULTS: Our results showed that PM2.5 exposure induced accumulation of lipid droplets in LUAD cells which accompanied by increased malignant cellular behaviors. PM2.5 exposure led to cleaved N-SREBP1 translocation into nucleus, which activated the de novo lipogenesis pathway. Same changes were also observed in normal lung epithelial cells and normal lung tissue, and mice developed pulmonary fibrosis after long-term exposure to PM2.5. Furthermore, in a cohort of 11,712 lung cancer patients, significant lipid metabolism disorders were observed in higher PM2.5 polluted areas. In view of that, D-limonene was found to inhibit the changes in lipid metabolism through upregulating the expression of miR-195, which inhibited the expression of lipogenic genes (SREBF1/FASN/ACACA) specifically. And a small human intervention trial showed that serum miR-195 was upregulated after oral intake of D-limonene. CONCLUSION: Our findings reveal a new mechanism of pulmonary fibrosis and LUAD that is related to PM2.5 exposure-induced lipid droplet accumulation. We also demonstrate that D-limonene-miR-195-SREBP1/FASN axis is a potential preventive intervention for mediating the progression and development of LUAD induced by PM2.5 exposure. Trial registration Chinese Clinical Trial Registry, ChiCTR2000030200. Registered 25 February 2020, http://www.chictr.org.cn/showproj.aspx?proj=48013.

Protocol for an open-label, single-arm, multicentre clinical study to evaluate the efficacy and safety of rituximab in the first episode of paediatric idiopathic nephrotic syndrome.

INTRODUCTION: Rituximab (RTX) effectively prevents relapses in patients with complicated steroid-sensitive nephrotic syndrome (SSNS). The 1-year relapse-free survival rate is approximately 30% in children after the first episode of SSNS treated with standardised corticosteroids. Whether the benefits of RTX extend to the first relapse are unknown. The efficacy and safety of RTX in the first episode of paediatric idiopathic nephrotic syndrome (RTXFIRPedINS) trial (NCT04783675) will assess its effect on the risk of subsequent relapse. METHODS AND ANALYSIS: RTXFIRPedINS is an open-label, single-arm, multicentre trial targeting patients aged 1-18 years with a first episode of SSNS. All patients will receive standardised corticosteroid treatment for 12 weeks. A sample size of 44 patients provides 80% power to detect a 20% increase in the 1-year relapse-free rate, assuming a dropout rate of 10%. After obtaining informed consent and screening, eligible patients will be treated with a single intravenous infusion of 375 mg/m2 RTX within 1 week after achieving remission. Trimethoprim-sulfamethoxazole will be administered for 3 months after RTX administration to prevent Pneumocystis carinii infection. The follow-up period will be 1 year. The primary outcome is the 1-year relapse-free survival rate after RTX infusion. The secondary study outcomes are the number of days from the infusion of RTX to the occurrence of the first relapse, 6-month relapse-free survival rate, the B cell recovery time and treatment-related adverse events. Immunological factors will be studied as predictors of response. ETHICS AND DISSEMINATION: This trial was approved by the Ethics Committee of the Children's Hospital of Fudan University and seven local ethics committees. We will publish our study results in peer-reviewed journals and present them at international scientific meetings. TRIAL REGISTRATION NUMBER: NCT04783675.

Panoramic quality assessment tool for investigator initiated trials.

Objectives: Quality can be a challenge for Investigator initiated trials (IITs) since these trials are scarcely overseen by a sponsor or monitoring team. Therefore, quality assessment for departments managing clinical research grants program is important and urgently needed. Our study aims at developing a handy quality assessment tool for IITs that can be applied by both departments and project teams. Methods: The framework of the quality assessment tool was developed based on the literature studies, accepted guidelines and the Delphi method. A total of 272 ongoing IITs funded by Shanghai non-profit organizations in 2015 and 2016 were used to extract quality indexes. Confirmatory factor analysis (CFA) was used to further evaluate the validity and feasibility of the conceptual quality assessment tool. Results: The tool consisted of 4 critical quality attributes, including progress, quality, regulation, scientificity, and 13 observed quality indexes. A total of 257 IITs were included in the validity and feasibility assessment. The majority (60.29%) were Randomized Controlled Trial (RCT), and 41.18% were multi-center studies. In order to test the validity and feasibility of IITs quality assessment tool, CFA showed that the model fit the data adequately. (CMIN/DF = 1.868, GFI = 0.916; CFI = 0.936; TLI = 0.919; RMSEA = 0.063; SRMR = 0.076). Different types of clinical studies fit well in the tool. However, RCT scored lower than prospective cohort and retrospective study in enrollment progress (7.02 vs. 7.43, 9.63, respectively). Conclusion: This study established a panoramic quality assessment tool based on the Delphi method and CFA, and the feasibility and effectiveness of the tool were verified through clinical research examples. The use of this tool can help project management departments effectively and dynamically manage research projects, rationally allocate resources, and ensure the quality of IITs.

Development of an Active Surveillance or Surgery Model to Predict Lymph Node Metastasis in cN0 Papillary Thyroid Microcarcinoma.

Objective: Involvement of multiple lymph node (LN) metastasis in papillary thyroid microcarcinoma (PTMC) may indicate a progressive disease. To assist treatment decision, we conducted a clinical study to develop and validate a prediction model for the preoperative evaluation of LN metastasis involving more than five lymph nodes in patients with clinical N0 (cN0) PTMC. Material and Methods: Using data from 6,337 patients with cN0 PTMCs at Tianjin Medical University Cancer Institute and Hospital from 2013 to 2017, we identified and integrated risk factors for the prediction of multiple LN metastasis to build a nomogram. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. The model was validated using bootstrap resampling of the training cohort and an independent temporal validation cohort at the same institution. Results: In the training cohort (n = 3,209 patients), six independent risk factors were identified and included the prediction model (PTMC Active Surveillance or Surgery (ASOS) Model), including age, gender, multifocality, tumor size, calcification, and aspect ratio. The PTMC ASOS model was validated both internally and through the temporal validation cohort (n = 3,128 patients) from the same institute. The C-indexes of the prediction model in the training cohort were 0.768 (95% CI, 0.698-0.838), 0.768 and 0.771 in the internal validation and external validation cohorts, respectively. The area under the receiver operating characteristic curve (AUC) was 0.7068 and 0.6799. The calibration curve for probability of large-LN metastasis showed good agreement between prediction by nomogram and actual observation. DCA curves were used for comparison with another model, and IDI and NRI were also calculated. The cutoff value of our model was obtained by the ROC curve. Based on this model and cut point, a web-based dynamic nomogram was developed (https://tjmuch-thyroid.shinyapps.io/PTMCASOSM/). Conclusion: We established a novel nomogram that can help to distinguish preoperatively cN0 PTMC patients with or without metastasis of multiple lymph nodes. This clinical prediction model may be used in decision making for both active surveillance and surgery.

Human Umbilical Cord Mesenchymal Stem Cells to Treat Neuromyelitis Optica Spectrum Disorder (hUC-MSC-NMOSD): A Study Protocol for a Prospective, Multicenter, Randomized, Placebo-Controlled Clinical Trial.

Background: Neuromyelitis Optica spectrum disorder (NMOSD) is severe relapsing and disabling autoimmune disease of the central nervous system. Its optimal first-line treatment to reduce relapse rate and ameliorate neurological disability remains unclear. We will conduct a prospective, multicenter, randomized, placebo-controlled clinical trial to study the safety and effectiveness of human umbilical cord mesenchymal stem cells (hUC-MSCs) in treating NMOSD. Methods: The trial is planned to recruit 430 AQP4-IgG seropositive NMOSD patients. It consists of three consecutive stages. The first stage will be carried out in the leading center only and aims to evaluate the safety of hUC-MSCs. Patients will be treated with three different doses of hUC-MSCs: 1, 2, or 5 × 106 MSC/kg·weight for the low-, medium-, and high-dose group, respectively. The second and third stages will be carried out in six centers. The second stage aims to find the optimal dosage. Patients will be 1:1:1:1 randomized into the low-, medium-, high-dose group and the controlled group. The third stage aims to evaluate the effectiveness. Patients will be 1:1 randomized into the optimal dose and the controlled group. The primary endpoint is the first recurrent time and secondary endpoints are the recurrent times, EDSS scores, MRI lesion numbers, OSIS scores, Hauser walking index, and SF-36 scores. Endpoint events and side effects will be evaluated every 3 months for 2 years. Discussion: Although hUC-MSC has shown promising treatment effects of NMOSD in preclinical studies, there is still a lack of well-designed clinical trials to evaluate the safety and effectiveness of hUC-MSC among NMOSD patients. As far as we know, this trial will be the first one to systematically demonstrate the clinical safety and efficacy of hUC-MSC in treating NMOSD and might be able to determine the optimal dose of hUC-MSC for NMOSD patients. Trial registration: The study was registered with the Chinese Clinical Trial Registry (CHICTR.org.cn) on 2 March 2016 (registration No. ChiCTR-INR-16008037), and the revised trial protocol (Protocol version 1.2.1) was released on 16 March 2020.

A Novel Signature of Lipid Metabolism-Related Gene Predicts Prognosis and Response to Immunotherapy in Lung Adenocarcinoma.

Background: Lipid metabolism disorder, a new hallmark of cancer initiation, has been involved in lung adenocarcinoma (LUAD). However, few biomarkers about lipid metabolism-related genes (LMRGs) have been developed for prognosis prediction and clinical treatment of LUAD patients. Methods: In this study, we constructed and validated an effective prognostic prediction model for LUAD patients depending on LMRGs. Subsequently, we investigated the prediction model from immune microenvironment, genomic changes, and immunotherapy. Results: Then, eleven LMRGs were identified and applied to LUAD subtyping. In comparison with the high-risk group, the low-risk group exhibited a remarkably favorable prognosis, along with a higher immune score and lower tumor purity. Moreover, the low-risk group presented higher levels of immune checkpoint molecules, lower tumor immune dysfunction and exclusion (TIDE) score and tumor mutation burden (TMB), and higher likelihood of benefiting from immunotherapy. Furthermore, the genomic changes of six LMRGs (CD79A, HACD1, CYP17A1, SLCO1B3, ANGPTL4, and LDHA) were responsible for the difference in susceptibility to LUAD by greatly influencing B-cell activation. Conclusion: Generally speaking, the LMRG model is a reliable independent biomarker for predicting adverse outcomes in LUAD patients and has the potential to facilitate risk-stratified immunotherapy.

Development and evaluation of cancer differentiation analysis technology: a novel biophysics-based cancer screening method.

BACKGROUND: Routine health checkup is an essential strategy for monitoring population health and maintaining healthy workforces. However, there was a lack of cancer screening tests among routine health checkups due to high costs and unreliable methods. METHODS: We conducted a two-stage study to evaluate the value of a blood test, Cancer Differentiation Analysis (CDATM), which is developed to differentiate the blood samples of healthy individuals from those of cancer patients through measuring and analyzing multiple biophysical properties. RESULTS: The first stage of a cross-sectional study included 75,942 healthy individuals in routine health checkup, and the second stage of a prospective population-based cohort included 1,957 healthy community members. Forty-eight and ten cancer cases were identified among cross-sectional study and prospective population-based cohort, respectively. Using a pre-determined cutoff, we found that the CDA™ test could differentiate blood samples between healthy and cancer individuals with >93% specificity and >55% sensitivity in both studies. CONCLUSIONS: With high specificity and moderate sensitivity of CDA™ test, our study indicates that we can analyze biophysical properties in the blood to rapidly and reliably screen healthy individuals from cancer patients in a health checkup setting where most individuals are healthy or with average risk of cancer.

The Design and Rationale of a Multicentre Randomised Controlled Trial Comparing Transperineal Percutaneous Laser Ablation With Transurethral Resection of the Prostate for Treating Benign Prostatic Hyperplasia.

Background: Transurethral resection of the prostate (TURP) is regarded as the "gold standard" for the treatment of benign prostatic hyperplasia (BPH) in elderly men. However, ~15% of patients who had undergone TURP had intraoperative and postoperative complications, such as bleeding, urinary incontinence and urethral stricture. Transperineal percutaneous laser ablation (TPLA) is a method that places the optical fibre directly into the prostate with the guidance of ultrasound imaging, and the percutaneous transperineal approach is performed distal to the urethra and rectum to protect these structures and reduce urethral or postoperative infection. Several studies on TPLA for BPH treatment have been reported recently; however, high-quality randomised controlled trial (RCT) to evaluate its efficacy, safety, and long-term follow up remain absent. Methods: This study is a multicentre, open-label RCT to assess the efficacy and safety of TPLA vs. TURP to treat BPH. We hypothesise that the TPLA has non-inferior efficacy to TURP in the International Prostate Symptom Score (IPSS) at 3 months changing from the baseline and lower incidence of post-surgery complications. One hundred and fourteen patients with BPH will be recruited at 19 sites and randomly assigned at 1:1 to TPLA or TURP groups. The patients will be followed up at 1, 3, 6, 12, and 24 months after the procedure. Discussion: The study will be the first multicentre clinical trial including 16 participating centres in China, Italy, Switzerland, and Poland with relatively large sample size 114. By comprehensively compare the safety and efficacy of TPLA with TURP in patients with BPH, especially concerning the improvement of lower urinary tract symptoms (LUTS) and complication incidence, the study will help to illustrate the clinical value of TPLA and provide a beneficial alternative treatment for BPH patients. Clinical Trial Registration: The study has been registered on Chinese Clinical Trial Registry (http://www.chictr.org.cn), identifier [ChiCTR1900022739].

Stratification of lung adenocarcinoma patients for d-limonene intervention based on the expression signature genes.

Globally, lung cancer ranks as the most lethal malignant neoplasm. d-Limonene, a plant extract enriched with essential oils, has been reported to exert anti-cancer effects both in vitro and in vivo; however, its clinical effect on humans remains elusive. Therefore, the present study aimed to investigate the gene expression signature that would potentially stratify lung adenocarcinoma (LUAD) patients who may benefit from d-limonene intervention, thus facilitating the development of newer treatment strategies for LUAD. In total, 1877 significant differentially expressed genes (DEGs) were identified. These genes were mainly associated with the metabolism of terpenoids and polyketides, lipid metabolism, endocrine system, carbohydrate metabolism, and cell growth and death pathways. Three genes, including antioncogenes FZD3 and MTURN, and oncogene PRC1, which were regulated by d-limonene were identified based on survival analysis of TCGA-LUAD data and were validated by both in vitro and in vivo experiments. High-risk patients screened by the model exhibited a significantly poor prognosis. In conclusion, three gene expression signatures (FZD3, MTURN, and PRC1) were validated by both in vitro and in vivo experiments and identified to help stratify candidate lung adenocarcinoma patients who may benefit from d-limonene intervention. Although further studies are warranted, this study highlighted a potential strategy to improve the treatment outcomes of LUAD patients.

Increasing Gap Between Thyroid Cancer Incidence and Mortality in Urban Shanghai, China: An Analysis Spanning 43 Years.

OBJECTIVE: To examine the secular trends of thyroid cancer incidence and mortality and to estimate the proportion of thyroid cancer cases potentially attributable to overdiagnosis. METHODS: Data on thyroid cancer cases from 1973 to 2015 were obtained from the Shanghai Cancer Registry. The average annual percent change (AAPC) was evaluated using the joinpoint regression analysis. The age, period, and birth cohort effects were assessed using an age-period-cohort model. The overdiagnosis of thyroid cancer cases was estimated based on the difference between observed and expected incidences using the rates of Nordic countries as reference. RESULTS: From 1973 to 2015, the number of thyroid cancer cases was 23 117, and 75% of the patients were women. The age-standardized rates were seven- to eightfold higher from 2013 to 2015 than from 1973 to 1977. Compared with relatively stable mortality, thyroid cancer incidence was dramatically increased from 2002 to 2015 in both sexes, with significant trends (men: AAPC = 21.84%, 95% CI: 18.77%-24.98%, P < .001; women: AAPC = 18.55%, 95% CI: 16.49%-20.64%, P < .001). The proportion of overdiagnosis has gradually increased over time, rising from 68% between 2003 and 2007 to more than 90% between 2013 and 2015. This increasing trend appeared to be similar between men and women. CONCLUSION: An increasing gap between thyroid cancer incidence and mortality was observed in Shanghai, and overdiagnosis has contributed substantially to the rise of incidence, which calls for an urgent update on the practice of thyroid examination.

Transcriptome Based Estrogen Related Genes Biomarkers for Diagnosis and Prognosis in Non-small Cell Lung Cancer.

BACKGROUND: Lung cancer is the tumor with the highest morbidity and mortality, and has become a global public health problem. The incidence of lung cancer in men has declined in some countries and regions, while the incidence of lung cancer in women has been slowly increasing. Therefore, the aim is to explore whether estrogen-related genes are associated with the incidence and prognosis of lung cancer. METHODS: We obtained all estrogen receptor genes and estrogen signaling pathway genes in The Cancer Genome Atlas (TCGA), and then compared the expression of each gene in tumor tissues and adjacent normal tissues for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) separately. Survival analysis was performed of the differentially expressed genes in LUAD and LUSC patients separately. The diagnostic and prognostic values of the candidate genes were validated in the Gene Expression Omnibus (GEO) datasets. RESULTS: We found 5 estrogen receptor genes and 66 estrogen pathway genes in TCGA. A total of 50 genes were differently expressed between tumor tissues and adjacent normal tissues and 6 of the 50 genes were related to the prognosis of LUAD in TCGA. 56 genes were differently expressed between tumor tissues and adjacent normal tissues and none of the 56 genes was related to the prognosis of LUSC in TCGA. GEO datasets validated that the 6 genes (SHC1, FKBP4, NRAS, PRKCD, KRAS, ADCY9) had different expression between tumor tissues and adjacent normal tissues in LUAD, and 3 genes (FKBP4, KRAS, ADCY9) were related to the prognosis of LUAD. CONCLUSIONS: The expressions of FKBP4 and ADCY9 are related to the pathogenesis and prognosis of LUAD. FKBP4 and ADCY9 may serve as biomarkers in LUAD screening and prognosis prediction in clinical settings.