Established and Validated Novel Nomogram for Predicting Prognosis of Post-Mastectomy pN0-1 Breast Cancer without Adjuvant Radiotherapy.
Ontology highlight
ABSTRACT: Aim
To establish and validate a nomogram for predicting prognosis of breast cancer patients with pN0-1 who were treated with mastectomy and without adjuvant radiotherapy.Material and methods
The LASSO regression was performed to identify predictors of breast cancer-specific survival (BCSS), local regional recurrence (LRR) and distant metastasis (DM). Model performance was evaluated by the concordance index (C-index) and calibration plot.Results
The 5-year BCSS, LRR and DM rates for the entire cohort were 98%, 2% and 4%, respectively. LASSO regression analysis found that pathological T stage, number of positive LN, grade and Ki-67 were significant predictors for both BCSS and DM-free survival, while number of resected LN and PR status were predictors for DM-free survival. In addition, number of positive LN was the only significant predictor for developing LRR. The C-indexes for the 5-year BCSS and DM nomograms were 0.81 and 0.78 in the training data set, 0.65 and 0.70 in the testing set and 0.72 and 0.69 in the external validation set, respectively.Conclusion
Our prognostic nomograms accurately predict 5-year BCSS and DM-free survival in post-mastectomy breast cancer without adjuvant radiotherapy, which provides a useful tool to identify high-risk patients who could benefit from additional adjuvant therapy.
SUBMITTER: Qi WX
PROVIDER: S-EPMC8079251 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Although adjuvant chemoradiotherapy for resected gallbladder cancer may improve survival for some patients, identifying which patients will benefit remains challenging because of the rarity of this disease. The specific aim of this study was to create a decision aid to help make individualized estimates of the potential survival benefit of adjuvant chemoradiotherapy for patients with resected gallbladder cancer.Patients with resected gallbladder cancer were selected from the Surveillance, Epidemiology, and End Results (SEER) -Medicare database who were diagnosed between 1995 and 2005. Covariates included age, race, sex, stage, and receipt of adjuvant chemotherapy or chemoradiotherapy (CRT). Propensity score weighting was used to balance covariates between treated and untreated groups. Several types of multivariate survival regression models were constructed and compared, including Cox proportional hazards, Weibull, exponential, log-logistic, and lognormal models. Model performance was compared using the Akaike information criterion. The primary end point was overall survival with or without adjuvant chemotherapy or CRT.A total of 1,137 patients met the inclusion criteria for the study. The lognormal survival model showed the best performance. A Web browser-based nomogram was built from this model to make individualized estimates of survival. The model predicts that certain subsets of patients with at least T2 or N1 disease will gain a survival benefit from adjuvant CRT, and the magnitude of benefit for an individual patient can vary.A nomogram built from a parametric survival model from the SEER-Medicare database can be used as a decision aid to predict which gallbladder patients may benefit from adjuvant CRT.
| S-EPMC3236647 | biostudies-other
Project description:PURPOSE:This study aimed to identify predictors for distant metastatic behavior and build a related prognostic nomogram in breast cancer. Materials and Methods:A total of 1,181 patients with non-metastatic breast cancer between 2003 and 2011 were analyzed. To predict the probability of distant metastasis, a nomogram was constructed based on prognostic factors identified using a Cox proportional hazards model. RESULTS:The 7-year overall survival and 5-year post-progression survival of locoregional versus distant recurrence groups were 67.6% versus 39.1% (p=0.027) and 54.2% versus 33.5% (p=0.043), respectively. Patients who developed distant metastasis showed early and late mortality risk peaks within 3 and after 5 years of follow-up, respectively, but a broad and low risk increment was observed in other patients with locoregional relapse. In multivariate analysis of distant metastasis-free interval, age (? 45 years vs. < 45 years), molecular subtypes (luminal A vs. luminal B, human epidermal growth receptor 2, and triple negative), T category (T1 vs. T2-3 and T4), and N category (N0 vs. N1 and N2-3) were independently associated (p < 0.05 for all). Regarding the significant factors, a well-validated nomogram was established (concordance index, 0.812). The risk score level of patients with initial brain failure was higher than those of non-brain sites (p=0.029). CONCLUSION:The nomogram could be useful for predicting the individual probability of distant recurrence in breast cancer. In high-risk patients based on the risk scores, more aggressive systemic therapy and closer surveillance for metastatic failure should be considered.
| S-EPMC6192903 | biostudies-literature
Project description:Background: To explore the effects of postoperative adjuvant transarterial chemoembolization (PA-TACE) on the prognosis of HCC patients with Portal Vein Tumor Thrombus (PVTT) undergoing resection, and to develop a PA-TACE-related nomogram for predicting survival individually. Patients and Methods: Two hundred and ninety-three consecutive HCC patients with PVTT under R0 hepatectomy were recruited. Forty-seven cases had recurrence within one month after surgery. The remaining 246 cases consisted of 90 PA-TACE and 156 non-PA-TACE cases. COX regression analysis was performed for overall survival (OS) or recurrence-free survival (RFS) of these 246 cases, allowing the derivation of independent factors that were integrated into the nomogram. C-index, calibration curves, and risk stratification were performed to evaluate the performance and discriminative power of the nomograms. Results: In 246 patients without recurrence within one month after surgery, the OS and RFS for the PA-TACE group were significantly better than those for the non-PA-TACE group (P<0.0001, P<0.0001, respectively). After Cox regression analysis of OS or RFS, PA-TACE-related nomogram models were constructed. The C-index of the PA-TACE-related nomogram for OS and RFS was 0.72 and 0.73, respectively. Calibration curves revealed a good agreement between predictions and observations for the nomograms. Based on the nomogram-related risk stratification, Kaplan-Meier curves showed powerful discriminative ability. Conclusions: PA-TACE therapy improved the survival of HCC patients with PVTT undergoing hepatectomy. Accurate nomogram models were developed for predicting the individual survival and recurrence of these patients.
| S-EPMC7645989 | biostudies-literature
Project description:ObjectiveThe aim of this study was to examine the predictive value of the multiplication of neutrophil and monocyte counts (MNM) in peripheral blood, and develop a new predictive model for the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH).MethodsThis is a retrospective analysis that included 2 separate cohorts of patients undergoing endovascular coiling for aSAH. The training cohort consisted of 687 patients in the First Affiliated Hospital of Shantou University Medical College; the validation cohort consisted of 299 patients from Sun Yat-sen University's Affiliated Jieyang People's Hospital. The training cohort was used to develop 2 models to predict unfavorable prognosis (modified Rankin scale of 3-6 at 3 months): one was based on traditional factors (e.g., age, modified Fisher grade, NIHSS score, and blood glucose), and another model that included traditional factors as well as MNM on admission.ResultsIn the training cohort, MNM upon admission was independently associated with unfavorable prognosis (odds ratio after adjustment, 1.06; 95% confidence interval [CI], 1.03-1.10). In the validation cohort, the basic model that included only traditional factors had 70.99% sensitivity, 84.36% specificity, and 0.859 (95% CI, 0.817-0.901) area under the receiver operating characteristic curve (AUC). Adding MNM increased model sensitivity (from 70.99% to 76.48%), specificity (from 84.36% to 88.63%), and overall performance (AUC 0.859 [95% CI, 0.817-0.901] to 0.879 [95% CI, 0.841-0.917]).InterpretationMNM upon admission is associated with unfavorable prognosis in patients undergoing endovascular embolization for aSAH. The nomogram including MNM is a user-friendly tool to help clinicians quickly predict the outcome of patients with aSAH.
| S-EPMC10351672 | biostudies-literature
Project description:PurposeYoung age is associated with poor prognosis in ductal carcinoma in situ (DCIS) of female breast and controversy exists regarding the optimal treatment modality for young patients. We aimed to compare treatment outcomes among breast conserving surgery (BCS), BCS with adjuvant radiotherapy (BCS + RT), and total mastectomy (MT) for young DCIS women.MethodsPubMed, Cochrane, and Embase were searched for studies reporting comparative results among BCS, BCS + RT, or MT in ≤50 years old (y/o) DCIS females. Study quality was assessed and meta-analysis with subgroup analysis was performed to pool the effect sizes of the outcomes-of-interest.ResultsWe included 3 randomized control trials and 18 observational studies. For DCIS women ≤50 y/o, RT following BCS significantly reduced the risk for ipsilateral breast tumor recurrence (IBTR) (HR = 0.66, 95% CI 0.50-0.87). However, the benefit was less robust in extremely young patients and with long follow-ups. RT revealed no statistically significant preventive effect on ipsilateral invasive recurrence (HR = 1.38, 95% CI 0.98-1.94). On the other hand, MT yielded the lowest IBTR (BCS + RT vs MT: HR = 4.4, 95% CI 2.06-9.40), both in ipsilateral DCIS recurrence and ipsilateral invasive recurrence. There was great heterogeneity and could not reach an evident conclusion concerning survival outcomes.ConclusionThis study highlighted the varying effect of RT for young DCIS females. The local control benefit of MT was definite without survival differences observed. Our study provided a moderate certainty of evidence to guide the treatment for young DCIS women. Further age-specific prospective trial is warranted.
| S-EPMC8927828 | biostudies-literature
Project description:PurposeThe prognosis of liver cancer remains unfavorable nowadays, making the search for predictive biomarkers of liver cancer prognosis of paramount importance to guide clinical diagnosis and treatment. This study was conducted to explore more prognostic markers for most HCC.Patients and methodsA total of 330 patients were enrolled in this study according to the inclusion and exclusion criteria. Follow-up data were collected for all patients until the cutoff date of the study, February 2023. In addition, patient outcomes were assessed with progression-free survival (PFS) and overall survival (OS). All statistical analysis was conducted using R 4.2.0 software.ResultsUnivariate analysis illustrated that the GD [the product of gamma-glutamyl transpeptidase (GGT) concentration and D-dimer concentration, GD=GGT*D-dimer] levels were related to PFS (p<0.05) and OS (p<0.05). Kaplan-Meier survival curves and log-rank tests indicated a significant difference among different levels of GD (p<0.001). Multivariate analysis demonstrated GD as an independent prognostic factor for HCC. The C-indexes of nomogram were 0.77 and 0.76 in the training or validation cohort, respectively. Area Under the Curve (AUC) of 1-, 2-, 3-, and 4-year OS showed satisfactory accuracy, and the calibration curve illustrated brilliant consistence between the ideal and predicted values.ConclusionsHerein, it was demonstrated that GD was an independent prognostic factor for HCC and revealed the potential to predict the PFS and OS in patients with HCC. Moreover, the nomogram based on GD illustrated a satisfactory prediction ability in comparison to other models without GD.
| S-EPMC10646613 | biostudies-literature
Project description:From March 2003 to April 2004, 77 physicians throughout France prospectively recruited 1289 ductal carcinoma in situ (DCIS) patients and collected data on diagnosis, patient and tumour characteristics, and treatments. Median age was 56 years (range, 30-84). Ductal carcinoma in situ was diagnosed by mammography in 87.6% of patients. Mastectomy, conservative surgery alone (CS) and CS with radiotherapy (CS+RT) were performed in 30.5, 7.8 and 61.7% of patients, respectively. Thus, 89% of patients treated by CS received adjuvant RT. Sentinel node biopsy (SNB) and axillary dissection (AD) were performed in 21.3 and 10.4% of patients, respectively. Hormone therapy was administered to 13.4% of the patients (80% tamoxifen). Median tumour size was 14.5 mm (6, 11 and 35 mm for CS, CS+RT and mastectomy, respectively, P<0.0001). Nuclear grade was high in 21% of patients, intermediate in 38.5% and low in 40.5%. Excision was considered complete in 92% (CS) and 88.3% (CS+RT) of patients. Oestrogen receptors were positive in 69.8% of assessed cases (31%). Treatment modalities varied widely according to region: mastectomy rate, 20-37%; adjuvant RT, 84-96%; hormone treatment, 6-34%. Our survey on current DCIS management in France has highlighted correlations between pathological features (tumour size, margin and grade) and treatment options, with several similar variations to those observed in recent UK and US studies.
| S-EPMC2670007 | biostudies-literature
Project description:BackgroundThe optimal tool for predicting the survival of renal cell carcinoma (RCC) patients with lung metastases remains controversial.MethodsWe selected patients diagnosed with RCC and lung metastases, from 2010 to 2015, from the Surveillance, Epidemiology, and End Results (SEER) database. After the selection of inclusion criteria and exclusion criterion, the rest of the patients were incorporated into model analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to select the most important features for construction of a nomogram predicting cancer-specific survival. A calibration plot and the concordance index (C-index) were used to estimate nomogram efficacy in a validation cohort. The association between important factors selected by LASSO regression, and prognosis was assessed by the Kaplan-Meier (KM) survival curve. The receiver operating characteristic (ROC) curves were drawn to compare sensitivity and specificity between the nomogram we built and the TNM stage-based model.ResultsA total of 1,369 patients met the inclusion criteria, but not the exclusion criteria. The LASSO regression model reduced 15 features to seven potential predictors of survival, including tumor grade, the extent of surgery, N and T status, histological profile, and brain and bone metastasis status. Such features had good discrimination in the KM survival curves. The nomogram showed excellent discriminatory power (C-index, 0.71; 95% confidence interval: 0.70 to 0.72) and good calibration in terms of both 1- and 2-year cancer-specific survival. The nomogram showed great discriminatory power (C-index 0.68) and adequate calibration when applied to the validation cohort. The areas under the curve (AUCs) of nomogram were 0.767 and 0.780, respectively, and the AUCs of TNM stage were 0.617 and 0.618 at 1 and 2 years, respectively.ConclusionsOur nomogram might play a major role in predicting the cancer-specific survival of RCC patients with lung metastases.
| S-EPMC7997741 | biostudies-literature
Project description:BackgroundRecent international sequencing efforts have allowed for the molecular taxonomy of lower-grade gliomas (LGG). We sought to analyze The Cancer Genome Atlas (TCGA, 2015) gene expression datasets on molecularly defined oligodendrogliomas (IDH-mutated and 1p/19q-codeleted) patients treated with adjuvant radiation or those observed to discover prognostic markers and pathways.MethodsmRNA expression and clinical information of patients with oligodendroglioma were taken from the TCGA "Brain Lower Grade Glioma" provisional dataset. Transcription factor network reconstruction and analysis were performed using the R packages "RTN" and "RTNsurvival." Elastic net regularization and survival modeling were performed using the "biospear," "plsRCox," "survival" packages.ResultsFrom our cohort of 137 patients, 65 received adjuvant radiation and 72 were observed. In the cohort that received adjuvant radiotherapy, a transcription factor activity signature, that correlated with hypoxia, was associated with shorter disease-free survival (DFS) (median = 45 months vs 108 months, P < .001). This increased risk was not seen in patients who were observed (P = .2). Within the observation cohort, a transcription factor activity signature was generated that was associated with poor DFS (median = 72 months. vs 143 months., P < .01).ConclusionsWe identified a transcription factor activity signature associated with poor prognosis in patients with molecular oligodendroglioma treated with adjuvant radiotherapy. These patients would be potential candidates for treatment intensification. A second signature was generated for patients who were more likely to progress on observation. This potentially identifies a cohort who would benefit from upfront adjuvant radiotherapy.
| S-EPMC8099467 | biostudies-literature
Project description:PurposeTo investigate the risk factors for recurrence in patients with early-stage hepatocellular carcinoma (HCC) after minimally invasive treatment with curative intent, then to construct a prediction model based on Lasso-Cox regression and visualize the model built.MethodsClinical data were collected from 547 patients that received minimally invasive treatment in our hospital from January 1, 2012, to December 31, 2016. Lasso regression was used to screen risk factors for recurrence. Then we established Cox proportional hazard regression model and random survival forest model including several parameters screened by Lasso regression. An optimal model was selected by comparing the values of C-index, then the model was visualized and the nomogram was finally plotted.ResultsThe variables screened by Lasso regression including age, gender, cirrhosis, tumor number, tumor size, platelet-albumin-bilirubin index (PALBI), and viral load were incorporated in the Cox model and random survival forest model (P<0.05). The C-index of these two models in the training sets was 0.729 and 0.708, and was 0.726 and 0.700 in the validation sets, respectively. So we finally chose Lasso-Cox regression model, and the calibration curve in the validation set performed well, indicating that the model built has a better predictive ability. And then a nomogram was plotted based on the model chosen to visualize the results.ConclusionsThe present study established a nomogram for predicting recurrence in patients with early-stage HCC based on the Lasso-Cox regression model. This nomogram was of some guiding significance for screening populations at high risk of recurrence after treatment, by which doctors can formulate individualized follow-up strategies or treatment protocols according to the predicted risk of relapse for patients to improve the long-term prognosis.
| S-EPMC9726717 | biostudies-literature