In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This...In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.展开更多
To learn the subgroup structure generated by multidimensional interaction, we propose a novel multiview subgroup integration technique based on tensor decomposition. Compared to the traditional subgroup analysis that ...To learn the subgroup structure generated by multidimensional interaction, we propose a novel multiview subgroup integration technique based on tensor decomposition. Compared to the traditional subgroup analysis that can only handle single-view heterogeneity, our proposed method achieves a greater level of homogeneity within the subgroups, leading to enhanced interpretability and predictive power. For computational readiness of the proposed method, we build an algorithm that incorporates pairwise shrinkage-encouraging penalties and ADMM techniques. Theoretically, we establish the asymptotic consistency and normality of the proposed estimators. Extensive simulation studies and real data analysis demonstrate that our proposal outperforms other methods in terms of prediction accuracy and grouping consistency. In addition, the analysis based on the proposed method indicates that intergenerational care significantly increases the risk of chronic diseases associated with diet and fatigue in all provinces while only reducing the risk of emotion-related chronic diseases in the eastern coastal and central regions of China.展开更多
In this article,a new unit level model based on a pairwise penalised regression approach is proposed for problems in small area estimation(SAE).Instead of assuming common regression coefficients for all small domains ...In this article,a new unit level model based on a pairwise penalised regression approach is proposed for problems in small area estimation(SAE).Instead of assuming common regression coefficients for all small domains in the traditional model,the new estimator is based on a subgroup regression model which allows different regression coefficients in different groups.The alternating direction method of multipliers(ADMM)algorithm is used to find subgroups with different regression coefficients.We also consider pairwise spatial weights for spatial areal data.In the simulation study,we compare the performances of the new estimator with the traditional small area estimator.We also apply the new estimator to urban area estimation using data from the National Resources Inventory survey in Iowa.展开更多
BACKGROUND The primary complication associated with gestational diabetes mellitus(GDM)is delivery of an infant that is large for gestational age(LGA).Epidemiological findings have demonstrated that irregular lipid met...BACKGROUND The primary complication associated with gestational diabetes mellitus(GDM)is delivery of an infant that is large for gestational age(LGA).Epidemiological findings have demonstrated that irregular lipid metabolism significantly con-tributes to insulin resistance,a key pathophysiological mechanism in GDM.However,the correlation between various lipid indices and the probability of delivering LGA infants remains inconsistent.AIM To explore the relationships between lipid indices and the possibility of having LGA infants among GDM-affected pregnant females.METHODS Binary logistic regression methods were employed to evaluate the odds ratios and corresponding 95%confidence intervals for LGA according to five lipid indices.Restricted cubic spline models were applied to investigate dose-response relationships.The association between lipid indices and the risk of delivering LGA infants was further investigated among different subgroups.Receiver operating characteristic curves were utilized to assess the diagnostic performance of lipid indices.RESULTS Across crude and adjusted models,females with lipid indices in the upper two tertiles presented a markedly elevated risk of delivering LGA infants compared with the lowest tertile category.Conversely,high-density lipoprotein cholesterol levels demonstrated the contrary trend.Restricted cubic spline analyses revealed linear associations between the five lipid indices,except triglyceride levels,and the prevalence of LGA.The subgroup analysis highlighted that the correlation between lipid indices and the probability of LGA was inconsistent.The five lipid indices presented significant diagnostic efficacy,as indicated by receiver operating characteristic curve areas.CONCLUSION Our research demonstrated that lipid indices were effective predictors of the incidence of LGA infants in GDM-affected pregnancies irrespective of potential confounding factors.展开更多
Objective:Colorectal cancer(CRC)surgeries can be performed using either laparoscopic or open laparotomy approaches.However,the long-term outcomes based on tumor location and age remain unclear.This study compared the ...Objective:Colorectal cancer(CRC)surgeries can be performed using either laparoscopic or open laparotomy approaches.However,the long-term outcomes based on tumor location and age remain unclear.This study compared the long-term outcomes of laparoscopic and laparotomy surgeries in patients with CRC,focusing on tumor location and age to identify suitable subgroups and determine an optimal cut-off age.Methods:This retrospective study analyzed 2,014 patients with CRC who underwent radical surgery.Patients were categorized into laparoscopy and laparotomy groups,and propensity score matching(PSM)was performed.Kaplan-Meier analysis,log-rank tests,and Cox regression models were used to identify the independent factors affecting overall survival(OS).Results:Analysis results before PSM indicated higher OS in the laparoscopy group(P=0.035);however,it was no significant difference in mean OS between the two groups after PSM analysis.Cox regression analysis identified several factors influencing the OS of patients with CRC,with age,T stage,nodal involvement,poorly differentiated adenocarcinoma,ascites,preoperative intestinal obstruction,and local tumor spread as independent risk factors.Family history was a protective factor[hazard ratio(HR)=0.33;95%CI,0.16-0.68;P=0.002],and the surgical modality did not independently affect OS.The subgroup analysis highlighted the advantages of laparoscopic surgery in specific subgroups.Conclusions:Overall,laparoscopic and laparotomy surgeries resulted in similar mid-and long-term prognoses for patients with CRC.Laparoscopic surgery showed better outcomes in specific subgroups,particularly in patients aged>60 years and in those with right-sided colon carcinoma.This study suggests that age>64 years might be the optimal cut-off age for laparoscopic surgery.展开更多
Meta-analysis is an important statistical tool,and it is often used to solve clinical problems.However inevitably when conducting a meta-analysis,the included studies often have heterogeneity.This paper suggests the i...Meta-analysis is an important statistical tool,and it is often used to solve clinical problems.However inevitably when conducting a meta-analysis,the included studies often have heterogeneity.This paper suggests the inclusion of relevant background data or contextual variables into the model.The contextual variables are those variables not explicitly measured in the studies included in a metaanalysis;thus,these must be very well-described and justified as parameters for analyses.展开更多
Objective To assess relationships between cold spells and genitourinary hospitalization risk.Methods Hospitalization records for genitourinary system diseases(GUDs)from 16 districts in Beijing(2013–2018)were analyzed...Objective To assess relationships between cold spells and genitourinary hospitalization risk.Methods Hospitalization records for genitourinary system diseases(GUDs)from 16 districts in Beijing(2013–2018)were analyzed.Cold spells were defined based on varying intensity thresholds.A two-stage analytical method was employed:first,generalized linear models assessed district-specific associations between cold spells and hospitalizations;second,random-effects meta-analysis aggregated the districtlevel results.Subgroup analyses were performed by admission type(emergency vs.outpatient),age,and sex.Results A total of 271,579 GUD-related hospitalizations were recorded.Cold spells(p1day2,daily mean temperature below the 1st percentiles of the daily mean temperature distribution from January 1,2013,to December 31,2018,lasting for two or more consecutive days)were linked to a significant rise in hospitalization risks:1.43(95%CI:1.32–1.56)for all GUDs,1.35(95%CI:1.23–1.49)for urinary system diseases,and 1.46(95%CI:1.28–1.67)for renal failure,when compared to non-cold spell days.Emergency admissions showed higher risk increases than outpatient admissions.Conclusion Extreme cold spells significantly elevate hospitalization risks for GUDs.This highlights the urgent need for targeted public health interventions to mitigate cold-related health impacts,especially for vulnerable populations.展开更多
基金Supported by the Natural Science Foundation of Fujian Province(2022J011177,2024J01903)the Key Project of Fujian Provincial Education Department(JZ230054)。
文摘In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.
基金supported by National Key R&D Program of China (Grant No. 2022YFA1003702)National Natural Science Foundation of China (Grant Nos. 11931014 and 12271441)New Cornerstone Science Foundation
文摘To learn the subgroup structure generated by multidimensional interaction, we propose a novel multiview subgroup integration technique based on tensor decomposition. Compared to the traditional subgroup analysis that can only handle single-view heterogeneity, our proposed method achieves a greater level of homogeneity within the subgroups, leading to enhanced interpretability and predictive power. For computational readiness of the proposed method, we build an algorithm that incorporates pairwise shrinkage-encouraging penalties and ADMM techniques. Theoretically, we establish the asymptotic consistency and normality of the proposed estimators. Extensive simulation studies and real data analysis demonstrate that our proposal outperforms other methods in terms of prediction accuracy and grouping consistency. In addition, the analysis based on the proposed method indicates that intergenerational care significantly increases the risk of chronic diseases associated with diet and fatigue in all provinces while only reducing the risk of emotion-related chronic diseases in the eastern coastal and central regions of China.
基金This research was supported in part by the Natural ResourcesConservation Service of the U.S. Department of Agriculture.
文摘In this article,a new unit level model based on a pairwise penalised regression approach is proposed for problems in small area estimation(SAE).Instead of assuming common regression coefficients for all small domains in the traditional model,the new estimator is based on a subgroup regression model which allows different regression coefficients in different groups.The alternating direction method of multipliers(ADMM)algorithm is used to find subgroups with different regression coefficients.We also consider pairwise spatial weights for spatial areal data.In the simulation study,we compare the performances of the new estimator with the traditional small area estimator.We also apply the new estimator to urban area estimation using data from the National Resources Inventory survey in Iowa.
基金Supported by Nanjing Medical Science and Technique Development Foundation,No.YKK23151the Opening Foundation of Key Laboratory,No.JSHD202313+3 种基金Yingke Xinchuang Research Foundation of Jiangsu Blood Transfusion Association,No.JSYK2024006the Jiangsu Province Capability Improvement Project through Science,Technology and Education,No.ZDXYS202210Open Project of the State Key Laboratory of Reproductive Medicine of Nanjing Medical University,No.SKLRM-K202107the Jiangsu Provincial Maternal and Child Health Research Program,No.F202040.
文摘BACKGROUND The primary complication associated with gestational diabetes mellitus(GDM)is delivery of an infant that is large for gestational age(LGA).Epidemiological findings have demonstrated that irregular lipid metabolism significantly con-tributes to insulin resistance,a key pathophysiological mechanism in GDM.However,the correlation between various lipid indices and the probability of delivering LGA infants remains inconsistent.AIM To explore the relationships between lipid indices and the possibility of having LGA infants among GDM-affected pregnant females.METHODS Binary logistic regression methods were employed to evaluate the odds ratios and corresponding 95%confidence intervals for LGA according to five lipid indices.Restricted cubic spline models were applied to investigate dose-response relationships.The association between lipid indices and the risk of delivering LGA infants was further investigated among different subgroups.Receiver operating characteristic curves were utilized to assess the diagnostic performance of lipid indices.RESULTS Across crude and adjusted models,females with lipid indices in the upper two tertiles presented a markedly elevated risk of delivering LGA infants compared with the lowest tertile category.Conversely,high-density lipoprotein cholesterol levels demonstrated the contrary trend.Restricted cubic spline analyses revealed linear associations between the five lipid indices,except triglyceride levels,and the prevalence of LGA.The subgroup analysis highlighted that the correlation between lipid indices and the probability of LGA was inconsistent.The five lipid indices presented significant diagnostic efficacy,as indicated by receiver operating characteristic curve areas.CONCLUSION Our research demonstrated that lipid indices were effective predictors of the incidence of LGA infants in GDM-affected pregnancies irrespective of potential confounding factors.
基金Supported by National Natural Science Foundation of China,No.81270476the Priority Academic Program Development of Jiangsu Higher Education Institutions,JX10231801
文摘AIM: To quantify the association between Helicobacter pylori (H. pylori) infection and migraine.
基金supported by the Beijing Medical Award Foundation(No.YXJL-2023-0670-0150)。
文摘Objective:Colorectal cancer(CRC)surgeries can be performed using either laparoscopic or open laparotomy approaches.However,the long-term outcomes based on tumor location and age remain unclear.This study compared the long-term outcomes of laparoscopic and laparotomy surgeries in patients with CRC,focusing on tumor location and age to identify suitable subgroups and determine an optimal cut-off age.Methods:This retrospective study analyzed 2,014 patients with CRC who underwent radical surgery.Patients were categorized into laparoscopy and laparotomy groups,and propensity score matching(PSM)was performed.Kaplan-Meier analysis,log-rank tests,and Cox regression models were used to identify the independent factors affecting overall survival(OS).Results:Analysis results before PSM indicated higher OS in the laparoscopy group(P=0.035);however,it was no significant difference in mean OS between the two groups after PSM analysis.Cox regression analysis identified several factors influencing the OS of patients with CRC,with age,T stage,nodal involvement,poorly differentiated adenocarcinoma,ascites,preoperative intestinal obstruction,and local tumor spread as independent risk factors.Family history was a protective factor[hazard ratio(HR)=0.33;95%CI,0.16-0.68;P=0.002],and the surgical modality did not independently affect OS.The subgroup analysis highlighted the advantages of laparoscopic surgery in specific subgroups.Conclusions:Overall,laparoscopic and laparotomy surgeries resulted in similar mid-and long-term prognoses for patients with CRC.Laparoscopic surgery showed better outcomes in specific subgroups,particularly in patients aged>60 years and in those with right-sided colon carcinoma.This study suggests that age>64 years might be the optimal cut-off age for laparoscopic surgery.
文摘Meta-analysis is an important statistical tool,and it is often used to solve clinical problems.However inevitably when conducting a meta-analysis,the included studies often have heterogeneity.This paper suggests the inclusion of relevant background data or contextual variables into the model.The contextual variables are those variables not explicitly measured in the studies included in a metaanalysis;thus,these must be very well-described and justified as parameters for analyses.
基金supported by the National Natural Science Foundation of China(Grant Nos.92043301,41907367,41961134033)the National High-level Talents Special Support Plan of China for Young Talents.
文摘Objective To assess relationships between cold spells and genitourinary hospitalization risk.Methods Hospitalization records for genitourinary system diseases(GUDs)from 16 districts in Beijing(2013–2018)were analyzed.Cold spells were defined based on varying intensity thresholds.A two-stage analytical method was employed:first,generalized linear models assessed district-specific associations between cold spells and hospitalizations;second,random-effects meta-analysis aggregated the districtlevel results.Subgroup analyses were performed by admission type(emergency vs.outpatient),age,and sex.Results A total of 271,579 GUD-related hospitalizations were recorded.Cold spells(p1day2,daily mean temperature below the 1st percentiles of the daily mean temperature distribution from January 1,2013,to December 31,2018,lasting for two or more consecutive days)were linked to a significant rise in hospitalization risks:1.43(95%CI:1.32–1.56)for all GUDs,1.35(95%CI:1.23–1.49)for urinary system diseases,and 1.46(95%CI:1.28–1.67)for renal failure,when compared to non-cold spell days.Emergency admissions showed higher risk increases than outpatient admissions.Conclusion Extreme cold spells significantly elevate hospitalization risks for GUDs.This highlights the urgent need for targeted public health interventions to mitigate cold-related health impacts,especially for vulnerable populations.
