Background:Colorectal liver metastasis(CRLM)has a poor prognosis,and traditional prognostic models have certain limitations in clinical application.This study aims to evaluate the prognostic value of CT-based habitat ...Background:Colorectal liver metastasis(CRLM)has a poor prognosis,and traditional prognostic models have certain limitations in clinical application.This study aims to evaluate the prognostic value of CT-based habitat analysis in CRLM patients and compare it with existing traditional prognostic models to provide more evidence for individualized treatment of CRLM patients.Methods:This retrospective study included 197 patients with CRLM whose preoperative contrast-enhanced CT images and corresponding DICOM Segmentation Objects(DSOs)were obtained from The Cancer Imaging Archive(TCIA).Tumor regions were segmented,and habitat features representing distinct subregions were extracted.An unsupervised K-means clustering algorithm classified the tumors into two clusters based on their habitat characteristics.Kaplan–Meier analysis was used to evaluate overall survival(OS),disease-free survival(DFS),and liver-specific DFS.The habitat model's predictive performance was compared with the Clinical Risk Score(CRS)and Tumor Burden Score(TBS)using the concordance index(C-index),Integrated Brier Score(IBS),and time-dependent area under the curve(AUC).Results:The habitat model identified two distinct patient clusters with significant differences in OS,DFS,and liverspecific DFS(p<0.01).Compared with CRS and TBS,the habitat model demonstrated superior predictive accuracy,particularly for DFS and liver-specific DFS,with higher time-dependent AUC values and improved model calibration(lower IBS).Conclusions:CT-based habitat analysis captures spatial tumor heterogeneity and provides enhanced prognostic stratification in CRLM.The method outperforms conventional models and offers potential for more personalized treatment planning.展开更多
Despite the lack of predictive biomarkers and a prognostic stratification strategy,immune checkpoint inhibitor(ICI)has shown promise in improving outcomes for patients with limited-stage small cell lung cancer(LS-SCLC...Despite the lack of predictive biomarkers and a prognostic stratification strategy,immune checkpoint inhibitor(ICI)has shown promise in improving outcomes for patients with limited-stage small cell lung cancer(LS-SCLC).We evaluated the potential of circulating tumor DNA(ctDNA)to dynamically predict outcomes in patients with LS-SCLC receiving concurrent chemoradiotherapy(CCRT)with or without consolidation ICI.We analyzed 490 serial samples collected from 144 LS-SCLC patients at baseline(t0),post-induction chemotherapy and pre-thoracic radiotherapy(t1),post-radiotherapy(t2),and progressive disease(t3).For 44 patients receiving consolidation ICI with serplulimab,an investigational PD-1 inhibitor,ctDNA dynamics during consolidation ICI were also assessed at multiple time points.Patients with undetectable ctDNA after CCRT had good outcomes with or without consolidation ICI,whereas ctDNA-positive patients at t2,indicating poor response to CCRT,derived survival benefit from consolidation ICI.Notably,ctDNA status at t1 appeared more predictive than at t2.A three-level risk stratification strategy integrating t1 ctDNA status with radiological tumor shrinkage identified a high-risk subgroup of patients who achieved significantly improved progression-free survival(PFS)(hazard ratio[HR],0.24;95%confidence interval[CI],0.08-0.75;p=0.014)and overall survival(OS)(HR,0.06;95%CI,0.00-0.42;p=0.001)from consolidation ICI,prioritizing CCRT plus consolidation ICI.Furthermore,maintaining ctDNA negativity during consolidation ICI was associated with favorable outcomes.These data provide valuable insights into the individualized management of LS-SCLC in the era of immunotherapy.展开更多
Objective:This study aimed to evaluate the prognostic value of the pretreatment systemic immune-inflammation index(SII)in non-metastatic nasopharyngeal carcinoma(NPC).Methods:We retrospectively analyzed the data of 83...Objective:This study aimed to evaluate the prognostic value of the pretreatment systemic immune-inflammation index(SII)in non-metastatic nasopharyngeal carcinoma(NPC).Methods:We retrospectively analyzed the data of 839 patients with non-metastatic NPC recruited from two independent institutions.The training-set cohort and the external validation-set cohort was comprised of 459 and 380 patients from each institution,respectively.The optimal cut-offvalue of SII was determined,and a prognostic risk stratification model was developed based on the training cohort and further assessed in the validation cohort.The propensity score matching(PSM)method was applied to minimize the confounding effects of unbalanced covariables.Results:The optimal cut-offvalue of the SII in the training cohort was 686,which was confirmed using the vali-dation cohort.Multivariate analysis showed that both before and after PSM,SII values>686 were independently associated with worse progression-free survival(PFS)ratio in both cohorts(before PSM,P=0.008 and P=0.008;after PSM,P=0.008 and P=0.007,respectively).Based on the analysis of independent prognostic factors of SII and N stage,we developed a categorical risk stratification model,which achieved significant discrimination among risk indexes associated with PFS and distant metastasis-free survival(DMFS)in the training cohort.There was no significant difference in PFS between RT alone and combined therapies within the low-and intermediate-risk groups(5-year PFS,77.5%vs.75.3%,P=0.275).Patients in the high-risk group who received concurrent chemoradiotherapy experienced superior PFS compared with those who received other therapies(5-year PFS,64.9%vs.40.3%,P=0.003).Conclusion:Pretreatment SII predicts PFS of patients with non-metastatic NPC.Prognostic risk stratification incorporating SII is instructive for selecting individualized treatment.展开更多
基金supported by Henan University Interdisciplinary Advanced Research Institute Construction Project(CX3070A0970005)Key Scientific Research Project of Higher Education Institutions(25A320014)+1 种基金Henan Provincial Medical Science and Technology Public Relations Program Provincial Ministerial Co-Construction Key Project(SBGJ202302093)Henan Provincial Medical Science and Technology Research Project(LHGJ20240406).
文摘Background:Colorectal liver metastasis(CRLM)has a poor prognosis,and traditional prognostic models have certain limitations in clinical application.This study aims to evaluate the prognostic value of CT-based habitat analysis in CRLM patients and compare it with existing traditional prognostic models to provide more evidence for individualized treatment of CRLM patients.Methods:This retrospective study included 197 patients with CRLM whose preoperative contrast-enhanced CT images and corresponding DICOM Segmentation Objects(DSOs)were obtained from The Cancer Imaging Archive(TCIA).Tumor regions were segmented,and habitat features representing distinct subregions were extracted.An unsupervised K-means clustering algorithm classified the tumors into two clusters based on their habitat characteristics.Kaplan–Meier analysis was used to evaluate overall survival(OS),disease-free survival(DFS),and liver-specific DFS.The habitat model's predictive performance was compared with the Clinical Risk Score(CRS)and Tumor Burden Score(TBS)using the concordance index(C-index),Integrated Brier Score(IBS),and time-dependent area under the curve(AUC).Results:The habitat model identified two distinct patient clusters with significant differences in OS,DFS,and liverspecific DFS(p<0.01).Compared with CRS and TBS,the habitat model demonstrated superior predictive accuracy,particularly for DFS and liver-specific DFS,with higher time-dependent AUC values and improved model calibration(lower IBS).Conclusions:CT-based habitat analysis captures spatial tumor heterogeneity and provides enhanced prognostic stratification in CRLM.The method outperforms conventional models and offers potential for more personalized treatment planning.
基金supported by the Beijing Municipal Science&Technology Commission(Z221100007422011)the CAMS Innovation Fund for Medical Sciences(2024-I2M-ZD-004)+2 种基金National High Level Hospital Clinical Research Funding(2022-CICAMS-80102022503)the Noncommunicable Chronic Diseases-National Science and Technology Major Project(2024ZD0520200 and 2024ZD0520202 to Z.J.W.)the Major Research Plan of National Natural Sciences Foundation of China(92474202 to Z.J.W.).
文摘Despite the lack of predictive biomarkers and a prognostic stratification strategy,immune checkpoint inhibitor(ICI)has shown promise in improving outcomes for patients with limited-stage small cell lung cancer(LS-SCLC).We evaluated the potential of circulating tumor DNA(ctDNA)to dynamically predict outcomes in patients with LS-SCLC receiving concurrent chemoradiotherapy(CCRT)with or without consolidation ICI.We analyzed 490 serial samples collected from 144 LS-SCLC patients at baseline(t0),post-induction chemotherapy and pre-thoracic radiotherapy(t1),post-radiotherapy(t2),and progressive disease(t3).For 44 patients receiving consolidation ICI with serplulimab,an investigational PD-1 inhibitor,ctDNA dynamics during consolidation ICI were also assessed at multiple time points.Patients with undetectable ctDNA after CCRT had good outcomes with or without consolidation ICI,whereas ctDNA-positive patients at t2,indicating poor response to CCRT,derived survival benefit from consolidation ICI.Notably,ctDNA status at t1 appeared more predictive than at t2.A three-level risk stratification strategy integrating t1 ctDNA status with radiological tumor shrinkage identified a high-risk subgroup of patients who achieved significantly improved progression-free survival(PFS)(hazard ratio[HR],0.24;95%confidence interval[CI],0.08-0.75;p=0.014)and overall survival(OS)(HR,0.06;95%CI,0.00-0.42;p=0.001)from consolidation ICI,prioritizing CCRT plus consolidation ICI.Furthermore,maintaining ctDNA negativity during consolidation ICI was associated with favorable outcomes.These data provide valuable insights into the individualized management of LS-SCLC in the era of immunotherapy.
文摘Objective:This study aimed to evaluate the prognostic value of the pretreatment systemic immune-inflammation index(SII)in non-metastatic nasopharyngeal carcinoma(NPC).Methods:We retrospectively analyzed the data of 839 patients with non-metastatic NPC recruited from two independent institutions.The training-set cohort and the external validation-set cohort was comprised of 459 and 380 patients from each institution,respectively.The optimal cut-offvalue of SII was determined,and a prognostic risk stratification model was developed based on the training cohort and further assessed in the validation cohort.The propensity score matching(PSM)method was applied to minimize the confounding effects of unbalanced covariables.Results:The optimal cut-offvalue of the SII in the training cohort was 686,which was confirmed using the vali-dation cohort.Multivariate analysis showed that both before and after PSM,SII values>686 were independently associated with worse progression-free survival(PFS)ratio in both cohorts(before PSM,P=0.008 and P=0.008;after PSM,P=0.008 and P=0.007,respectively).Based on the analysis of independent prognostic factors of SII and N stage,we developed a categorical risk stratification model,which achieved significant discrimination among risk indexes associated with PFS and distant metastasis-free survival(DMFS)in the training cohort.There was no significant difference in PFS between RT alone and combined therapies within the low-and intermediate-risk groups(5-year PFS,77.5%vs.75.3%,P=0.275).Patients in the high-risk group who received concurrent chemoradiotherapy experienced superior PFS compared with those who received other therapies(5-year PFS,64.9%vs.40.3%,P=0.003).Conclusion:Pretreatment SII predicts PFS of patients with non-metastatic NPC.Prognostic risk stratification incorporating SII is instructive for selecting individualized treatment.
