User-friendly prognostic model for rectal neuroendocrine tumours: In the era of precision management

In this letter,we explore into the potential role of the recent study by Zeng et al.Rectal neuroendocrine tumours(rNETs)are rare,originate from peptidergic neurons and neuroendocrine cells,and express corresponding markers.Although most rNETs patients have a favourable prognosis,the median survival period significantly decreases when high-risk factors,such as larger tumours,poorer differentiation,and lymph node metastasis exist,are present.Clinical prediction models play a vital role in guiding diagnosis and prognosis in health care,but their complex calculation formulae limit clinical use.Moreover,the prognostic models that have been developed for rNETs to date still have several limitations,such as insufficient sample sizes and the lack of external validation.A high-quality prognostic model for rNETs would guide treatment and follow-up,enabling the precise formulation of individual patient treatment and follow-up plans.The future development of models for rNETs should involve closer collab-oration with statistical experts,which would allow the construction of clinical prediction models to be standardized and robust,accurate,and highly general-izable prediction models to be created,ultimately achieving the goal of precision medicine.

Evaluation of a rabbit rectal VX2 carcinoma model using computed tomography and magnetic resonance imaging

AIM： To establish a rabbit rectal VX2 carcinoma model for the study of rectal carcinoma.METHODS： A suspension of VX2 cells was injected into the rectum wall under the guidance of X-ray fluoroscopy. Computed tomography （CT） and magnetic resonance imaging （MRI） were used to observe tumorgrowth and metastasis at different phases. Pathological changes and spontaneous survival time of the rabbits were recorded.RESULTS： Two weeks after VX2 cell implantation, the tumor diameter ranged 4.1-5.8 mm and the success implantation rate was 81.8%. CT scanning showed low-density loci of the tumor in the rectum wail, while enhanced CT scanning demonstrated a symmetrical intensification in tumor loci. MRI scanning showed alow signal of the tumor on T1-weighted imaging anda high signal of the tumor on T2-weighted imaging.Both types of signals were intensified with enhanced MRI. Metastases to the liver and lung could beobserved 6 wk after VX2 cell implantation, and a largearea of necrosis appeared in the primary tumor. The spontaneous survival time of rabbits with cachexia and multiple organ failure was about 7 wk after VX2 cell implantation.CONCLUSION： The rabbit rectal VX2 carcinoma model we established has a high stability, and can be used in the study of rectal carcinoma.

Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy

BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for clinical stage II/III rectal cancer.However,few patients achieve a complete pathological response,and most patients require surgical resection and adjuvant therapy.Therefore,identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival(OS)and disease-free survival(DFS)for LARC treated with NT.METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017.The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors,which were validated by the Cox regression method.Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves,and that of the two nomograms was conducted by calculating the concordance index(C-index)and calibration curves.The results were validated in a cohort of 65 patients from 2015 to 2017.RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model:Vascular_tumors_bolt,cancer nodules,yN,body mass index,matchmouth distance from the edge,nerve aggression and postoperative carcinoembryonic antigen.The nomogram showed good predictive value for OS,with a C-index of 0.91(95%CI:0.85,0.97)and good calibration.In the validation cohort,the C-index was 0.69(95%CI:0.53,0.84).The risk factor prediction model showed good predictive value.The areas under the curve for 3-and 5-year survival were 0.811 and 0.782.The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77(95%CI:0.69,0.85).In the validation cohort,the C-index was 0.71(95%CI:0.61,0.81).The prediction model for DFS also had good predictive value,with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

Current and future role of three-dimensional modelling technology in rectal cancer surgery:A systematic review

BACKGROUND Three-dimensional(3D)modelling technology translates the patient-specific anatomical information derived from two-dimensional radiological images into virtual or physical 3D models,which more closely resemble the complex environment encountered during surgery.It has been successfully applied to surgical planning and navigation,as well as surgical training and patient education in several surgical specialties,but its uptake lags behind in colorectal surgery.Rectal cancer surgery poses specific challenges due to the complex anatomy of the pelvis,which is difficult to comprehend and visualise.AIM To review the current and emerging applications of the 3D models,both virtual and physical,in rectal cancer surgery。METHODS Medline/PubMed,Embase and Scopus databases were searched using the keywords“rectal surgery”,“colorectal surgery”,“three-dimensional”,“3D”,“modelling”,“3D printing”,“surgical planning”,“surgical navigation”,“surgical education”,“patient education”to identify the eligible full-text studies published in English between 2001 and 2020.Reference list from each article was manually reviewed to identify additional relevant papers.The conference abstracts,animal and cadaveric studies and studies describing 3D pelvimetry or radiotherapy planning were excluded.Data were extracted from the retrieved manuscripts and summarised in a descriptive way.The manuscript was prepared and revised in accordance with PRISMA 2009 checklist.RESULTS Sixteen studies,including 9 feasibility studies,were included in the systematic review.The studies were classified into four categories:feasibility of the use of 3D modelling technology in rectal cancer surgery,preoperative planning and intraoperative navigation,surgical education and surgical device design.Thirteen studies used virtual models,one 3D printed model and 2 both types of models.The construction of virtual and physical models depicting the normal pelvic anatomy and rectal cancer,was shown to be feasible.Within the clinical context,3D models were used to identify vascular anomalies,for surgical planning and navigation in lateral pelvic wall lymph node dissection and in management of recurrent rectal cancer.Both physical and virtual 3D models were found to be valuable in surgical education,with a preference for 3D printed models.The main limitations of the current technology identified in the studies were related to the restrictions of the segmentation process and the lack of 3D printing materials that could mimic the soft and deformable tissues.CONCLUSION 3D modelling technology has potential to be utilised in multiple aspects of rectal cancer surgery,however,it is still at the experimental stage of application in this setting.

Magnetic resonance imaging-based deep learning model to predict multiple firings in double-stapled colorectal anastomosis

BACKGROUND Multiple linear stapler firings during double stapling technique(DST)after laparoscopic low anterior resection(LAR)are associated with an increased risk of anastomotic leakage(AL).However,it is difficult to predict preoperatively the need for multiple linear stapler cartridges during DST anastomosis.AIM To develop a deep learning model to predict multiple firings during DST anastomosis based on pelvic magnetic resonance imaging(MRI).METHODS We collected 9476 MR images from 328 mid-low rectal cancer patients undergoing LAR with DST anastomosis,which were randomly divided into a training set(n=260)and testing set(n=68).Binary logistic regression was adopted to create a clinical model using six factors.The sequence of fast spin-echo T2-weighted MRI of the entire pelvis was segmented and analyzed.Pure-image and clinical-image integrated deep learning models were constructed using the mask region-based convolutional neural network segmentation tool and three-dimensional convolutional networks.Sensitivity,specificity,accuracy,positive predictive value(PPV),and area under the receiver operating characteristic curve(AUC)was calculated for each model.RESULTS The prevalence of≥3 linear stapler cartridges was 17.7%(58/328).The prevalence of AL was statistically significantly higher in patients with≥3 cartridges compared to those with≤2 cartridges(25.0%vs 11.8%,P=0.018).Preoperative carcinoembryonic antigen level>5 ng/mL(OR=2.11,95%CI 1.08-4.12,P=0.028)and tumor size≥5 cm(OR=3.57,95%CI 1.61-7.89,P=0.002)were recognized as independent risk factors for use of≥3 linear stapler cartridges.Diagnostic performance was better with the integrated model(accuracy=94.1%,PPV=87.5%,and AUC=0.88)compared with the clinical model(accuracy=86.7%,PPV=38.9%,and AUC=0.72)and the image model(accuracy=91.2%,PPV=83.3%,and AUC=0.81).CONCLUSION MRI-based deep learning model can predict the use of≥3 linear stapler cartridges during DST anastomosis in laparoscopic LAR surgery.This model might help determine the best anastomosis strategy by avoiding DST when there is a high probability of the need for≥3 linear stapler cartridges.

Construction of a clinical survival prognostic model for middle-aged and elderly patients with stage III rectal adenocarcinoma

BACKGROUND Nomograms for prognosis prediction in colorectal cancer patients are few,and prognostic indicators differ with age.AIM To construct a new nomogram survival prediction tool for middle-aged and elderly patients with stage III rectal adenocarcinoma.METHODS A total of 2773 eligible patients were divided into the training cohort(70%)and the validation cohort(30%).Optimal cutoff values were calculated using the X-tile software for continuous variables.Univariate and multivariate Cox proportional hazards regression analyses were used to determine overall survival(OS)and cancer-specific survival(CSS)-related prognostic factors.Two nomograms were successfully constructed.The discriminant and predictive ability and clinical usefulness of the model were also assessed by multiple methods of analysis.RESULTS The 95%CI in the training group was 0.719(0.690-0.749)and 0.733(0.702-0.74),while that in the validation group was 0.739(0.696-0.782)and 0.750(0.701-0.800)for the OS and CSS nomogram prediction models,respectively.In the validation group,the AUC of the three-year survival rate was 0.762 and 0.770,while the AUC of the five-year survival rate was 0.722 and 0.744 for the OS and CSS nomograms,respectively.The nomogram distinguishes all-cause mortality from cancer-specific mortality in patients with different risk grades.The time-dependent AUC and decision curve analysis showed that the nomogram had good clinical predictive ability and decision efficacy and was significantly better than the tumor-node-metastases staging system.CONCLUSION The survival prediction model constructed in this study is helpful in evaluating the prognosis of patients and can aid physicians in clinical diagnosis and treatment.

Construction and validation of an immune-related lncRNA prognostic model for rectal adenocarcinomas

Objective This study aimed to construct a prognostic model for rectal adenocarcinomas based on immune-related long noncoding RNAs(lncRNAs)and verify its prediction efficiency.Methods Transcript data and clinical data of rectal adenocarcinomas were downloaded from The Cancer Genome Atlas(TCGA)database.Perl software(strawberry version)and R language(version 3.6.1)were used to analyze the immune-related genes and immune-related lncRNAs of rectal adenocarcinomas,and the differentially expressed immune-related lncRNAs were screened according to the criteria|log2FC|>1 and P<0.05.The key immune-related lncRNAs were screened using single-factor Cox regression analysis and lasso regression analysis.Multivariate Cox regression analysis was performed to construct an immune-related lncRNA prognostic model using the risk scores.Next,we evaluated the effectiveness of the model through Kaplan-Meier(K-M)survival analysis,ROC curve analysis,and independent prognostic analysis of clinical features.In addition,prognostic biomarkers of immune-related lncRNAs in the model were analyzed by K-M survival analysis.Results In this study,we obtained gene expression profile matrices of 89 rectal adenocarcinomas and 2 paracancerous specimens from TCGA database and applied immunologic signatures to these transcripts.Through R and Perl software analysis,we obtained 847 immune-related lncRNAs and 331 protein-encoded immune-related genes in rectal adenocarcinomas.Eight important immune-related lncRNAs related to the prognosis of rectal adenocarcinomas were identified using univariate Cox regression and lasso regression analysis.Furthermore,four immune-related lncRNAs were identified as prognostic markers of rectal adenocarcinomas via multivariate Cox regression analysis.The prognostic risk model was as follows:risk score=(-4.084)*expression LINC01871+(3.112)*expression AL158152.2+(7.616)*expression PXN-AS1+(-0.867)*expression HCP5.The independent prognostic effect of the rectal adenocarcinoma risk score model was revealed through K-M analysis,ROC curve analysis,and univariate,and multivariate Cox regression analysis(P=0.035).LINC01871(P=0.006),PXN-AS1(P=0.008),and AL158152.2(P=0.0386)were closely correlated with the prognosis of rectal adenocarcinomas through the K-M survival analysis.Conclusion We constructed a prognostic model of rectal adenocarcinomas based on four immune-related lncRNAs by analyzing the data based on TCGA database,with high prediction accuracy.We also identified two biomarkers with poor prognosis(PXN-AS1 and AL158152.2)and one biomarker with good prognosis(LINC01871).

Radiomics for predicting perineural invasion status in rectal cancer

BACKGROUND Perineural invasion(PNI),as a key pathological feature of tumor spread,has emerged as an independent prognostic factor in patients with rectal cancer(RC).The preoperative stratification of RC patients according to PNI status is beneficial for individualized treatment and improved prognosis.However,the preoperative evaluation of PNI status is still challenging.AIM To establish a radiomics model for evaluating PNI status preoperatively in RC patients.METHODS This retrospective study enrolled 303 RC patients in a single institution from March 2018 to October 2019.These patients were classified as the training cohort(n=242)and validation cohort(n=61)at a ratio of 8:2.A large number of intraand peritumoral radiomics features were extracted from portal venous phase images of computed tomography(CT).After deleting redundant features,we tested different feature selection(n=6)and machine-learning(n=14)methods to form 84 classifiers.The best performing classifier was then selected to establish Rad-score.Finally,the clinicoradiological model(combined model)was developed by combining Rad-score with clinical factors.These models for predicting PNI were compared using receiver operating characteristic curve(ROC)analysis and area under the ROC curve(AUC).RESULTS One hundred and forty-four of the 303 patients were eventually found to be PNIpositive.Clinical factors including CT-reported T stage(cT),N stage(cN),and carcinoembryonic antigen(CEA)level were independent risk factors for predicting PNI preoperatively.We established Rad-score by logistic regression analysis after selecting features with the L1-based method.The combined model was developed by combining Rad-score with cT,cN,and CEA.The combined model showed good performance to predict PNI status,with an AUC of 0.828[95%confidence interval(CI):0.774-0.873]in the training cohort and 0.801(95%CI:0.679-0.892)in the validation cohort.For comparison of the models,the combined model achieved a higher AUC than the clinical model(cT+cN+CEA)achieved(P<0.001 in the training cohort,and P=0.045 in the validation cohort).CONCLUSION The combined model incorporating Rad-score and clinical factors can provide an individualized evaluation of PNI status and help clinicians guide individualized treatment of RC patients.

Establishment,functional and genetic characterization of three novel patient-derived rectal cancer cell lines

AIM To establish patient-individual tumor models of rectal cancer for analyses of novel biomarkers, individual response prediction and individual therapy regimens.METHODS Establishment of cell lines was conducted by direct in vitro culturing and in vivo xenografting with subsequent in vitro culturing. Cell lines were in-depth characterized concerning morphological features, invasive and migratory behavior, phenotype, molecular profile including mutational analysis, protein expression, and confirmation of origin by DNA fingerprint. Assessment of chemosensitivity towards an extensive range of current chemotherapeutic drugs and of radiosensitivity was performed including analysis of a combined radioand chemotherapeutic treatment. In addition, glucose metabolism was assessed with 18 F-fluorodeoxyglucose(FDG) and proliferation with 18 F-fluorothymidine.RESULTS We describe the establishment of ultra-low passage rectal cancer cell lines of three patients suffering from rectal cancer. Two cell lines(HROC126, HROC284 Met) were established directly from tumor specimens while HROC239 T0 M1 was established subsequent to xenografting of the tumor. Molecular analysis classified all three cell lines as CIMP-0/non-MSI-H(sporadic standard) type. Mutational analysis revealed following mutational profiles: HROC126: APC^(wt), TP53^(wt), KRAS^(wt), BRAF^(wt), PTEN^(wt); HROC239 T0 M1: APC^(mut), P53^(wt), KRAS^(mut), BRAF^(wt), PTEN^(mut) and HROC284 Met: APC^(wt), P53^(mut), KRAS^(mut), BRAF^(wt), PTEN^(mut). All cell lines could be characterized as epithelial(EpCAM+) tumor cells with equivalent morphologic features and comparable growth kinetics. The cell lines displayed a heterogeneous response toward chemotherapy, radiotherapy and their combined application. HROC126 showed a highly radio-resistant phenotype and HROC284 Met was more susceptible to a combined radiochemotherapy than HROC126 and HROC239 T0 M1. Analysis of 18 F-FDG uptake displayed a markedly reduced FDG uptake of all three cell lines after combined radiochemotherapy. CONCLUSION These newly established and in-depth characterized ultra-low passage rectal cancer cell lines provide a useful instrument for analysis of biological characteristics of rectal cancer.

直肠癌淋巴结转移风险预测模型构建研究

目的构建直肠癌(RC)淋巴结转移(LNM)风险预测模型。方法回顾性选取浙江省人民医院2015年6月至2023年12月经根治性手术后病理检查证实为RC的患者745例,按7∶3比例分为训练集(用于模型构建)522例和验证集(用于模型验证)223例。比较训练集LNM阳性与阴性患者临床资料,采用多因素logistic回归模型分析训练集RC患者LNM影响因素,基于差异有统计学意义的影响因素绘制RC LNM风险预测模型的列线图,并采用ROC曲线、校准曲线、决策曲线分析和Bootstrap法进行模型验证。结果RC根治术后根据TNM分期将训练集患者分为LNM阳性224例和LNM阴性298例,LNM阳性与阴性患者在是否印戒细胞癌、组织学分级、T分期、癌胚抗原(CEA)、糖类抗原19-9(CA19-9)、血小板与淋巴细胞比值(PLR)等方面比较,差异均有统计学意义(均P<0.01)。组织学分级低或极低分化(OR=7.524)、T3~4(OR=3.421)、CEA>5 ng/mL(OR=1.652)、CA19-9>39 U/mL(OR=2.240)、PLR>132.5(OR=1.625)均是训练集RC患者LNM的独立危险因素(均P<0.05)。基于组织学分级、T分期、CEA、CA19-9、PLR构建的RC LNM风险预测模型在训练集、验证集中的AUC及95%CI分别为0.755(0.714~0.797)、0.705(0.636~0.774),提示具有较强的预测能力;校准曲线显示对LNM风险的预测概率和实际概率之间一致性高,提示具有良好的准确性和稳定性;决策曲线显示训练集、验证集的阈值概率分别为0~0.75、0~0.60,净收益率均远高于2条无效线,提示具有较强的临床适用性;Bootstrap法显示准确率为0.73,Kappa值为0.430,提示泛化能力较好。结论本研究基于组织学分级、T分期、CEA、CA19-9、PLR构建的RC LNM风险预测模型具有潜在的临床应用价值。

扩散加权成像联合动态增强磁共振扫描构建影像组学模型联合临床参数评估直肠癌分期

目的探究基于扩散加权成像联合多期动态增强提取纹理参数构建无侵袭性模型评估直肠癌分期的可行性。方法回顾性选取郑州大学第二附属医院2016年7月至2021年6月就诊的直肠癌患者为研究对象。所有患者的分期严格按照AJCC第8版进行分期,并分为早期组(Ⅰ~Ⅱ)和晚期组(Ⅲ~Ⅳ)。收集患者的年龄、性别、癌胚抗原(CEA)、糖类抗原199(CA199)等信息,所有患者均在获取病理资料前进行多期动态增强磁共振扫描以及磁共振弥散加权扫描,并计算血管渗透性参数(K_(trans)、K_(ep)、V_(e)、V_(p))以及表观弥散系数(ADC),基于动态增强磁共振影像提取影像组学参数、ADC、血管渗透性参数以及临床信息构建联合模型进行直肠癌的分期预测。结果本研究共纳入115例患者,训练组81例,测试组34例,以训练组患者的影像组学特征信息进行特征降纬,取惩罚系数log=0.0617时对应的特征个数进行影像组学模型构建,训练组Ⅰ~Ⅱ患者影像组学模型平均值为-0.4(-0.7~0),Ⅲ~Ⅳ组患者的影像组学模型的平均值为0.6(0.1~1.3);测试组Ⅰ~Ⅱ患者影像组学模型平均值为-0.1(-0.5~0.2),Ⅲ~Ⅳ组患者的影像组学模型的平均值为1.2(0.5~1.4);训练组和测试组中,Ⅰ~Ⅱ患者的影像组学模型低于Ⅲ~Ⅳ组患者,差异有统计学意义。分别针对Ⅰ~Ⅱ与Ⅲ~Ⅳ的非影像组学参数进行单因素逻辑回归分析后,V_(e)的OR值为0,ADC的OR值为0.04,联合两者进行临床模型构建。训练组中联合模型AUC为0.921,测试组中AUC为0.811。结论联合临床信息、ADC、血管渗透性参数与影像组学参数构建的联合模型可以协助临床上无侵袭性预测直肠癌患者分期信息。

腹腔镜直肠癌手术后发生腹直肌萎缩的影响因素分析及预测模型构建

目的:探讨腹腔镜直肠癌手术后发生腹直肌萎缩的影响因素,并构建预测模型。方法:回顾性选择2020年3月至2023年3月收治的行腹腔镜根治手术的229例直肠癌患者,收集临床相关资料,根据术后是否发生腹直肌萎缩将患者分为萎缩组(n=47)与对照组(n=182)。Logistic回归分析直肠癌腹腔镜手术后发生腹直肌萎缩的因素,受试者工作特征曲线构建直肠癌腹腔镜术后发生腹直肌萎缩的预测模型,Hosmer-Lemeshow检验预测模型的校准度。结果:多因素Logistic回归分析显示,年龄较大、术后长期卧床、预防性造口、术后化疗、术后并发手术部位感染是直肠癌腹腔镜手术后发生腹直肌萎缩的危险因素(P<0.05),高白蛋白水平是保护因素(P<0.05)。受试者工作特征曲线分析显示,预测模型预测直肠癌腹腔镜手术后发生腹直肌萎缩的曲线下面积为0.868(95%CI:0.817~0.909),灵敏度、特异度分别为85.11%与87.91%。Hosmer-Lemeshow检验显示预测模型具有较好的符合度(χ^(2)=3.251,P>0.05)。结论:年龄较大、术后长期卧床、预防性造口、术后化疗、手术部位感染、低白蛋白是直肠癌腹腔镜手术后腹直肌萎缩的相关因素,据此建立预测模型可较好地预测腹直肌萎缩风险。

中低位直肠癌根治术后实现教科书式结局的影响因素分析及预测模型的建立

目的 探讨中低位直肠癌根治术后实现教科书式结局(textbook outcome, TO)的影响因素。方法 回顾性分析2022年1月至2024年2月我院胃肠外科收治的182例中低位直肠癌患者的临床病理资料;TO定义为同时满足以下条件:无再次干预;肿瘤切缘阴性;术后住院时间≤14 d;30 d内无计划外再住院;90 d内无死亡;清扫淋巴结数目≥12枚;术后无严重并发症(Clavien-Dindo分级≥2)。结果 共计182例中低位直肠癌患者被纳入分析,其中123例(67.58%)患者术后实现了TO。所有患者均达到了肿瘤切缘阴性和90 d内无死亡;179例(98.35%)患者无再次干预,162例(89.01%)患者术后住院时间≤14 d, 181例(99.45%)患者30 d内无计划外再住院,163例(89.56%)患者清扫淋巴结数目≥12枚,123例(67.58%)患者术后无严重并发症。单因素分析结果显示,TO组与非TO组在手术方式、癌结节、NLR、PLR、SII方面比较,差异有统计学意义(P<0.05)。多因素分析结果显示,手术方式为Miles、存在癌结节、术前高SII是术后实现TO的独立影响因素(P<0.05)。结论 手术方式为Miles、存在癌结节、术前高SII是中低位直肠癌根治术后实现TO的独立影响因素。

直肠癌永久性结肠造口术患者延续护理中同伴支持模式的研究

目的探究直肠癌永久性结肠造口术患者延续护理中同伴支持模式的作用。方法选取(2022年1月至2022年12月)厦门大学附属第一医院收治的直肠癌永久性结肠造口术患者120例,以随机数字表法作为分组依据,均60例。对照组患者予以常规护理,观察组在常规护理的基础上予以延续护理中同伴支持模式。对比两组自护能力[自我护理能力量表(ESCA)]、生活质量[生命质量测定量表(QLQ-C30)]。结果护理后,观察组自护能力(自我护理技能、自我概念、健康知识、自我护理责任)高于对照组(P<0.05)。经护理,观察组角色功能、躯体功能、社会功能、认知功能、情绪功能分值高于对照组(P<0.05)。结论予以直肠癌永久性结肠造口术患者的延续护理联合同伴支持模式,不仅提升了患者的生存质量,增强其自我护理能力,同时也可改善患者预后,有效延长其生存时间。

基于ADOPT模式的团体心理干预对老年直肠癌患者自我管理能力、生活质量及希望水平的影响

目的 探讨基于ADOPT模式的团体心理干预对老年直肠癌患者自我管理能力、生活质量及希望水平的影响。方法 依据干预方法的不同将200例老年直肠癌患者分为观察组(n=109)和常规组(n=91),常规组患者给予常规干预,观察组患者给予基于ADOPT模式的团体心理干预。比较两组患者的造口适应情况[造口适应量表(OAS)]、自我管理能力、负性情绪[焦虑自评量表(SAS)和抑郁自评量表(SDS)]、生活质量[欧洲癌症研究与治疗组织生命质量测定量表(EORTC QLQ-C30)]、希望水平[Herth希望量表(HHI)]和满意度。结果 出院时和出院后6个月,两组患者OAS量表各维度评分和总分均高于本组术后1天,且观察组患者OAS量表各维度评分和总分均高于常规组,差异均有统计学意义(P﹤0.05)。出院时,两组患者SAS、SDS评分均低于本组术后1天,肠造口病人自我管理能力问卷、EORTC QLQ-C30、HHI量表各维度评分均高于本组术后1天,观察组患者SAS、SDS评分均低于常规组,肠造口病人自我管理能力问卷、EORTC QLQ-C30、HHI量表各维度评分均高于常规组,差异均有统计学意义(P﹤0.05)。观察组患者的总满意度为98.17%,明显高于常规组患者的89.01%,差异有统计学意义(P﹤0.01)。结论 基于ADOPT模式的团体心理干预可明显缓解老年直肠癌患者的负性情绪,强化患者适应情况和自我管理能力,提高生活质量、希望水平和满意度。

直肠癌新辅助放化疗疗效lncRNA分子预测模型构建

目的筛选直肠癌新辅助放化疗(CRT)疗效预测长链非编码RNA(lncRNA)分子标志物,分析参与CRT疗效调控相关信号通路,建立CRT疗效预测模型。方法利用lncRNA芯片进行lncRNA差异表达检测,使用R软件Limma包在CRT反应组和CRT无反应组间对比筛选差异lncRNA(P<0.05和|Log2FC|>1),进行分子标志物筛选。采用基因本体(GO)分析对差异表达基因进行功能分析,采用京都基因和基因组数据库(Kyoto Encyclopedia of Genes and Genomes,KEGG)对筛选的差异基因进行信号通路富集分析。进一步采用实时定量反转录聚合酶链式反应(qRT-PCR)检测98例样本。采用logistic回归构建CRT治疗预测模型。绘制受试者操作特征曲线(ROC)计算曲线下面积(AUC)以评价模型的判别区分能力。结果CRT反应组中,823个lncRNA表达上调,216个lncRNA表达下调,449个基因表达上调,81个基因表达下调。新辅助放化疗相关上调排名前10的差异表达lncRNA分别为LUCAT1、LINC02356、HIF1A-AS2、Lnc-ZNF644-1、Lnc-ADAMTS12-3、LINC02356、Lnc-CLIC4-1、Lnc-PTX3-4、DARS-AS1、MIR210HG。下调排名前10的分别为Lnc-COL6A3-2、Lnc-FBN1-2、Lnc-FOXA1-3、Lnc-KRTAP9-7-1、LINC00562、Lnc-NCS1-1、LINC00456、Lnc-FBLL1-2、USP2-AS1、Lnc-INPPL1-2。GO分析结果提示,差异基因主要富集在上皮细胞分化、中间丝、中间丝细胞骨架、突触后膜、颗粒分泌、细胞因子受体活性等分子生物学功能方面。KEGG富集分析提示,差异表达基因主要富集在HIF-1信号通路、Th17细胞分化、戊糖磷酸途径、精氨酸和脯氨酸代谢、果糖和甘露糖代谢、磷脂酶D信号通路、溶酶体等信号通路方面。logistic回归模型显示,由LUCAT1、LINC02356、LINC00562三个lncRNA分子构成的预测模型具有较好的预测能力,AUC为0.887(95%CI 0.820~0.954)。模型回归方程logit(p)=1.582×LINC00562-1.969×LINC02356-0.798×LUCAT1+4.357。模型的灵敏度为81.3%,特异度为84.0%。结论直肠癌CRT反应良好和CRT无反应者间lncRNA分子存在明显的差异表达,由LUCAT1、LINC02356、LINC00562三个lncRNA分子构成的预测模型对CRT疗效具有较好的预测能力。

基于T2WI和DWI的磁共振影像组学在术前预测直肠癌壁外血管侵犯的价值研究

目的:探讨基于磁共振(magnetic resonance imaging,MRI)T2加权成像(T2-weighted imaging,T2WI)和弥散加权成像(diffusion-weighted imaging,DWI)的影像组学,在术前预测直肠癌壁外血管侵犯(extramural vascular invasion,EMVI)的诊断效能。方法:回顾性收集2010年1月至2023年6月经术后病理证实为直肠腺癌且术前行直肠MRI扫描的患者168例,按7∶3随机分为训练集和验证集。提取T2WI、DWI的影像组学特征,采用最大相关最小冗余(the maximum relevance minimum redundancy,mRMR)和十倍交叉验证的最小绝对收缩与选择算子(the least absolute shrinkage and selection operator,LASSO)回归分析降维并选择影像组学特征,计算每例患者的影像组学总评分(Radscore),使用Radscore建立影像组学模型。在训练集中,研究纳入了3个临床特征[年龄、性别、术前癌胚抗原(carcinoembryonic antigen,CEA)]和6个磁共振影像学特征[ADC值、浸润深度、肿瘤长度、肿瘤部位、T分期、MRI壁外血管侵犯(magnetic resonance imaging-defined EMVI,mrEMVI)评分],通过单因素、多因素Logistic回归分析建立临床模型。联合Radscore和临床模型的独立危险因素,建立临床-影像组学模型(联合模型)。采用受试者操作特征(receiver operating characteristic,ROC)曲线评估各模型的诊断效能,通过DeLong检验比较不同模型的效能差异,采用校准曲线评估列线图术前预测结果与术后病理真实状况的拟合度,运用决策曲线分析(decision curve analysis,DCA)评价3种模型的临床应用价值。结果:联合模型、临床模型、影像组学模型ROC曲线在训练集和验证集中AUC分别为0.926、0.888、0.756和0.917、0.896、0.782,联合模型的诊断效能最佳。Delong检验显示,在训练集和验证集中,联合模型诊断效能高于影像组学模型(P<0.05);在训练集中,联合模型的诊断效能高于临床模型(P<0.05),但在验证集中差异无统计学意义(P>0.05)。校准曲线显示列线图术前预测结果与术后病理结果一致性良好(P<0.05)。DCA结果表明,当风险阈值概率在0.24~0.77时,联合模型在临床上的获益高于临床模型和影像组学模型。结论:基于T2WI和DWI的MRI影像组学模型术前预测直肠癌EMVI有较高的诊断效能,联合临床模型中独立危险因素构建的临床-影像组学MRI模型(联合模型)进一步提高了诊断效能。

多参数磁共振影像组学列线图在术前可有效预测直肠癌淋巴血管浸润

目的 探讨基于多参数磁共振影像组学结合临床危险因素构建的列线图模型在术前预测直肠癌淋巴血管浸润的价值。方法 回顾性分析蚌埠医学院第一附属医院术前行多参数MRI检查且术后病理证实为直肠腺癌的患者112例,收集患者的临床和盆腔影像资料,以7:3的比例随机分为训练集和验证集。通过单-多因素Logistic回归分析筛选与直肠癌淋巴血管浸润相关的临床独立危险因素;分别于T2WI、扩散加权成像和T1WI增强序列手动勾画感兴趣区并提取影像组学特征,经特征降维筛选最优影像组学特征构建影像组学模型;结合临床预测因子与影像组学评分标签构建列线图模型。采用ROC曲线下面积、校准曲线、决策曲线分析评价模型的预测效能。结果 列线图模型的预测效能最佳,其曲线下面积在训练集和验证集分别为0.876(95%CI:0.799~0.952)、0.769(95%CI:0.600~0.938),显著高于单独影像组学模型(0.818、0.741)和临床模型(0.714、0.548)。结论 本研究构建的列线图模型在预测直肠癌淋巴血管浸润方面具有较高的诊断性能,可以术前为临床决策提供重要指导。

极低位直肠癌腹腔镜经括约肌间切除术后肛门功能不良的影响因素及预测模型构建

目的分析极低位直肠癌腹腔镜经括约肌间切除术(Lap-ISR)术后肛门功能不良的影响因素,并以此构建预测模型并验证,以期为改善极低位直肠癌病人Lap-ISR术后肛门功能提供指导依据。方法回顾性选取2020年6月~2022年6月在泰州人民医院进行Lap-ISR手术的极低位直肠癌病人127例,术后对病人进行为期12个月的随访,用Wexner评分评估病人术后肛门功能,根据肛门失禁评分(Wexner)分为肛门功能良好组(106例)与肛门功能不良组(21例),收集病人临床资料并分析病人术后肛门功能不良的危险因素,并以此构建Nomogram列线图模型预测病人Lap-ISR术后肛门功能不良发生风险,并绘制受试者工作特征曲线(ROC),用曲线下面积(AUC)分析预测模型对病人Lap-ISR术后肛门功能不良的预测效能。结果极低位直肠癌病人Lap-ISR术后肛门功能不良发生率为16.54%(21/127)。单因素分析显示,两组性别、年龄、体质量指数、临床分期、合并基础疾病、手术时间、术中出血量、吻合方式、肿瘤下缘距齿状线距离比较差异均无统计学意义(P>0.05)。肛门功能不良组肿瘤直径≥5 cm占比、新辅助化疗占比、吻合口距肛缘距离<2 cm、吻合口漏占比均高于肛门功能良好组(P<0.05)。Cox多因素回归分析显示,肿瘤直径≥5 cm(OR=5.124)、新辅助化疗(OR=5.761)、吻合口漏(OR=6.881)是病人术后肛门功能的危险因素(P<0.05)。肿瘤直径≥5 cm病人Wexner评分高于肿瘤直径<5 cm病人,合并新辅助化疗Wexner评分高于无新辅助化疗病人,合并吻合口漏Wexner评分高于无吻合口漏病人(P<0.05)。Bootstrap法内部验证显示,C-index指数为0.785(95%CI:0.692~0.851)。ROC曲线结果显示,列线图模型预测病人术后肛门功能不良的灵敏度为85.70%、特异性为88.70%,AUC为0.895(95%CI:0.795~0.984)。结论肿瘤直径、新辅助化疗、吻合口漏是极低位直肠癌病人Lap-ISR术后肛门功能不良的危险因素。基于上述危险因素建立的列线图风险预测模型评估病人术后肛门功能不良的风险效能良好。

基于接纳与承诺理念的护理模式在直肠癌患者护理中的应用效果

目的:探讨基于接纳与承诺理念的护理模式在直肠癌患者护理中的应用效果。方法:选取2020年4月—2021年12月徐州市肿瘤医院收治的70例直肠癌患者作为研究对象,以随机数字表法分为两组,各35例。对照组接受常规护理,干预组采用基于接纳与承诺理念的护理模式。比较两组护理效果。结果:护理后,干预组Herth希望量表、创伤后成长问卷、主观幸福感量表各维度评分高于对照组,差异有统计学意义(P<0.05)。结论:基于接纳与承诺理念的护理模式在直肠癌患者护理中的应用效果理想,有利于提高患者内心希望水平与主观幸福感,帮助患者实现创伤后成长。