[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100630214":3},{"organization":4,"outcomesModule":7,"designInfo":18,"detailedDescription":21,"studyPopulation":22,"armGroups":17,"interventions":17,"overallOfficials":17,"centralContacts":17,"locations":17,"responsibleParty":23,"collaborators":17,"id":28,"slug":17,"hasResults":29,"nctId":30,"briefTitle":31,"officialTitle":32,"acronym":17,"eligibilityCriteria":33,"healthyVolunteers":29,"sex":34,"minAge":35,"maxAge":17,"enrollmentInfo":36,"targetDuration":17,"studyType":39,"phases":17,"briefSummary":40,"conditions":41,"keywords":43,"overallStatus":48,"whyStopped":17,"lastUpdateSubmitDate":49,"lastUpdatePostDateStruct":50,"startDateStruct":53,"completionDateStruct":55,"leadSponsor":57,"locationsCount":17},{"fullName":5,"class":6},"Shengjing Hospital","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":17},[9],{"measure":10,"description":11,"timeFrame":12},"Disease-free survival","Disease-free survival refers to the period from breast cancer excision to local recurrence, distant metastasis confirmed by clinical evidence, diagnosis of the second primary tumor or death of the patient.","5 years",[14],{"measure":15,"description":16,"timeFrame":12},"Overall survival","Overall survival refers to the time from breast cancer excision to death due to any cause",null,{"allocation":17,"interventionModel":17,"interventionModelDescription":17,"primaryPurpose":17,"observationalModel":19,"timePerspective":20,"maskingInfo":17},"COHORT","RETROSPECTIVE","Detailed Description Background and Rationale\n\nHormone receptor-positive\u002Fhuman epidermal growth factor receptor 2-negative (HR+\u002FHER2-) breast cancer constitutes approximately 70% of all breast cancer cases. Although early-stage patients generally have favorable outcomes following standard surgery and adjuvant endocrine therapy, long-term follow-up data reveal a distinct \"bimodal\" or \"long-tail\" recurrence pattern, with risks persisting for decades. Recent landmark trials (e.g., NATALEE, MonarchE) have established that combining CDK4\u002F6 inhibitors with endocrine therapy significantly improves invasive disease-free survival (iDFS) in high-risk populations. However, the stringent enrollment criteria of these randomized controlled trials may not fully capture the heterogeneity of real-world patients. Reliance on binary cut-off values (e.g., nodal status alone) risks misclassifying biologically high-risk individuals with low anatomical burden, leading to either undertreatment or overtreatment. There is an urgent clinical need for a multidimensional, individualized risk assessment tool to guide escalated therapy decisions.\n\nObjective\n\nTo develop and internally validate a nomogram integrating clinicopathological and lifestyle factors for predicting disease-free survival (DFS) in patients with HR+\u002FHER2- early breast cancer, and to evaluate its clinical utility using decision curve analysis (DCA).\n\nStudy Design\n\nThis is a single-center, retrospective cohort study based on real-world data. The study protocol has been approved by the Ethics Committee of Liaoning Cancer Hospital \\& Institute, and the requirement for informed consent was waived due to the retrospective nature of the study. All data will be de-identified prior to analysis to protect patient confidentiality.\n\nStudy Population\n\nPatients with histologically confirmed HR+\u002FHER2- early-stage breast cancer who received surgical treatment at Liaoning Cancer Hospital \\& Institute between July 2014 and June 2024 will be enrolled.\n\nData Collection and Variables\n\nDemographic, clinicopathological, and treatment-related variables will be extracted from the electronic medical record system. Variables to be collected include:\n\nDemographic characteristics: age, menopausal status\n\nPathological features: tumor size (T stage), lymph node status (N stage), histological grade, Ki-67 proliferation index, lymphovascular invasion (LVI)\n\nTreatment-related data: surgical procedure (breast-conserving surgery vs. mastectomy), chemotherapy (yes\u002Fno, regimen), endocrine therapy type (tamoxifen, aromatase inhibitor, etc.), radiotherapy (yes\u002Fno)\n\nLifestyle factors: duration of breastfeeding (months)\n\nFollow-up data: recurrence events (locoregional, distant), second primary cancers, vital status, and date of last follow-up\n\nThe primary endpoint is disease-free survival (DFS), defined as time from surgery to first recurrence (locoregional or distant), second primary cancer, or death from any cause.\n\nQuality Assurance and Data Validation\n\nA comprehensive quality assurance plan will be implemented to ensure data accuracy and completeness:\n\nData Verification: All data entered into the electronic case report form (eCRF) will be independently double-checked by two trained research assistants. Discrepancies will be resolved by consensus or by referral to a third reviewer.\n\nRange and Consistency Checks: Data will be validated against predefined rules (e.g., date consistency: diagnosis date ≤ surgery date ≤ last follow-up date; value ranges: Ki-67 0-100%, age \\>18 years). Automated logic checks will be programmed into the data entry system to flag outliers or inconsistencies.\n\nSource Data Verification: A random sample of 10% of patient records will be selected for source data verification against original medical records (paper or electronic) to assess accuracy and completeness. This will be performed by an independent data monitor not involved in primary data extraction.\n\nData Dictionary: A comprehensive data dictionary will be developed, containing detailed descriptions of each variable, including variable name, definition, source (e.g., pathology report, operative note), coding guidelines (e.g., AJCC 8th edition for TNM staging), permissible values, and normal ranges where applicable. This dictionary will be maintained and updated throughout the study.\n\nStandard Operating Procedures (SOPs)\n\nThe following SOPs will govern study operations:\n\nPatient Screening and Enrollment: SOP for identifying eligible patients from hospital databases and reviewing medical records.\n\nData Extraction and Entry: SOP detailing procedures for manual data abstraction, coding, and entry into the secure study database.\n\nData Management and Security: SOP for data storage, backup, access control, and de-identification to ensure compliance with institutional and national privacy regulations.\n\nAdverse Event Reporting: Although this is a retrospective observational study with no intervention, any serious adverse events identified during data collection that require reporting will follow institutional guidelines.\n\nChange Management: Any modifications to the protocol, data collection procedures, or analysis plan will be documented with version control and approved by the principal investigator.\n\nSample Size Assessment\n\nThe sample size for this study is determined by the availability of eligible patients diagnosed during the 10-year study period (July 2014 - June 2024). Based on institutional case volume, an estimated total of approximately 500-600 patients is expected.\n\nStatistical Analysis Plan\n\nAll statistical analyses will be performed using R software (version 4.1.0 or higher) and SPSS (version 24.0).\n\nDescriptive Analysis: Baseline characteristics will be summarized using frequencies and percentages for categorical variables, and means (with standard deviations) or medians (with interquartile ranges) for continuous variables, as appropriate. Comparisons between training and validation cohorts will be performed using chi-square tests (or Fisher's exact test) for categorical variables and t-tests (or Mann-Whitney U tests) for continuous variables.\n\nVariable Screening and Model Development:\n\nUnivariate Cox proportional hazards regression will be performed in the training cohort to screen potential predictors. Variables with P \\\u003C 0.10 will be considered for inclusion in the multivariate model to avoid excluding potentially important factors.\n\nMultivariate Cox regression with backward stepwise selection (based on Akaike Information Criterion, AIC) will be used to identify independent prognostic factors. Hazard ratios (HR) and 95% confidence intervals (CI) will be reported.\n\nA nomogram will be constructed based on the final multivariate Cox model, assigning points to each predictor proportional to its regression coefficient.\n\nModel Validation:\n\nDiscrimination: Model performance will be assessed using the concordance index (C-index) and time-dependent receiver operating characteristic (ROC) curve analysis with area under the curve (AUC) at 3 and 5 years.\n\nCalibration: Calibration plots will be generated comparing predicted versus observed survival probabilities at 3 and 5 years, using 1000 bootstrap resamples to estimate optimism.\n\nClinical Utility: Decision curve analysis (DCA) will be performed to evaluate the net clinical benefit of using the nomogram across a range of threshold probabilities for guiding escalated therapy decisions (e.g., recommending CDK4\u002F6 inhibitors), compared to \"treat-all\" or \"treat-none\" strategies.\n\nSensitivity Analyses: Subgroup analyses may be performed based on menopausal status or nodal status to explore model performance in clinically relevant subgroups.\n\nAll statistical tests will be two-sided, and a P-value \\\u003C 0.05 will be considered statistically significant unless otherwise specified.\n\nStudy Status\n\nThe study is currently in the protocol stage and has not yet begun data collection. Institutional ethics approval has been obtained. Data extraction and analysis are expected to commence upon registration.","We retrospectively collected data from patients with primary breast cancer who underwent surgical treatment at our center between July 2014 and June 2024.",{"type":24,"investigatorFullName":25,"investigatorTitle":26,"investigatorAffiliation":27,"oldNameTitle":17,"oldOrganization":17},"PRINCIPAL_INVESTIGATOR","Jianyi Li","Principal Investigator","Liaoning Cancer Hospital & Institute","100630214",false,"NCT07484763","Predicting Recurrence in HR+\u002FHER2- Early Breast Cancer","A Single-Center Retrospective Study to Develop a Nomogram for Predicting Recurrence in HR+\u002FHER2- Early Breast Cancer Using Real-World Data","Inclusion Criteria:\n\n* Histopathologically confirmed invasive breast ductal carcinoma or lobular carcinoma;\n* Molecular subtype of HR+\u002FHER2- (ER ≥ 10%, and HER2 immunohistochemistry 0\u002F1+ or 2+ without amplification confirmed by FISH);\n* Received standardized surgical treatment and postoperative adjuvant (or preoperative neoadjuvant) endocrine therapy;\n* Complete follow-up data available.\n\nExclusion Criteria:\n\n* Presence of distant metastasis (Stage IV) at diagnosis\n* Male breast cancer\n* Missing key clinicopathological data or loss to follow-up\n* HER2 immunohistochemistry 3+ or 2+ with amplification confirmed by FISH\n* Triple-negative breast cancer","FEMALE","18 Years",{"count":37,"type":38},500,"ESTIMATED","OBSERVATIONAL","Hormone receptor-positive\u002Fhuman epidermal growth factor receptor 2-negative (HR+\u002FHER2-) breast cancer constitutes approximately 70% of all breast cancer cases. Although early-stage patients generally have favorable outcomes following standard surgery and adjuvant endocrine therapy, long-term follow-up data reveal a distinct \"bimodal\" or \"long-tail\" recurrence pattern, with risks persisting for decades. Recent landmark trials (e.g., NATALEE, MonarchE) have established that combining CDK4\u002F6 inhibitors with endocrine therapy significantly improves invasive disease-free survival (iDFS) in high-risk populations. However, the stringent enrollment criteria of these randomized controlled trials may not fully capture the heterogeneity of real-world patients. Reliance on binary cut-off values (e.g., nodal status alone) risks misclassifying biologically high-risk individuals with low anatomical burden, leading to either undertreatment or overtreatment. There is an urgent clinical need for a multidimensional, individualized risk assessment tool to guide escalated therapy decisions.",[42],"Breast Cancer, HR+\u002FHER2- Early-Stage",[44,45,46,47],"Breast Cancer","HR+\u002FHER2-","Nomogram","Recurrence","NOT_YET_RECRUITING","2026-03-16",{"date":51,"type":52},"2026-03-20","ACTUAL",{"date":54,"type":38},"2026-04-01",{"date":56,"type":38},"2027-04-01",{"name":5,"class":6}]