Independent Factors for Poor Prognosis in Young Patients with Stage I-III Breast Cancer

Erić, Ivan; Erić, Anamarija Petek; Koprivčić, Ivan; Babić, Marko; Pačarić, Stana; Trogrlić, Bojan

doi:10.20471/acc.2020.59.02.07

Cited by 9 publications

(7 citation statements)

References 29 publications

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“…Age is a well-known prognostic factor for many tumors. [21][22][23] In patients with osteosarcoma, Hagleitner et al demonstrated that the 5-year OS rate for patients aged 20-40 years was 33.3% while 70.6% in ≤14 years old and 52.5% in 15-19 years old in a retrospective study of 102 osteosarcoma patients. 24 Moreover, Tsuchie et al compared the prognosis of primary osteosarcoma in younger and older patients based on a cut-off age of 40 and concluded that the older patients showed a poorer prognosis.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Liu¹,

He²,

Yao³

et al. 2021

IJGM

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Background The aim of the current study was to construct prognostic nomograms for individual risk prediction in elderly patients with osteosarcoma. Methods Data for 816 elderly patients (≥40 years old) with osteosarcoma between 2004 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were randomly assigned to training (N=573) and internal validation (N=243) sets. The essential clinical predictors were identified based on least absolute shrinkage and selection operator (Lasso) Cox regression. Nomograms were constructed to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS). Results Our LASSO regression analyses of the training set yielded five clinicopathological features (age, chemotherapy, surgery, AJCC stage, and summary stage) in the training cohort for the prognosis of elderly patients with osteosarcoma, while grade was only associated with OS and M stage was only associated with CSS. Construction of nomograms based on these predictors was performed to evaluate the prognosis of elderly patients with osteosarcoma. The C-index, calibration and decision curve analysis also showed the satisfactory performance of these nomograms for prognosis prediction. Conclusion The constructed nomograms are helpful tools for exactly predicting the prognosis of elderly patients with osteosarcoma, which could enable patients to be more accurately managed in clinical practice.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Liu¹,

He²,

Yao³

et al. 2021

IJGM

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“…also showed that non-ductal or lobular histological type (such as mucinous, medullary, tubular or metaplastic carcinoma) compared to invasive ductal or lobular type was associated with a lower risk of ALNM ( 38 , 39 ). A study showed that compared with older patients, young patients are more likely to have regional lymph node and distant metastasis ( 40 ). Other studies have considered age as an independent predictor of ALNM ( 27 – 29 , 41 ).…”

Section: Discussionmentioning

confidence: 99%

Nomogram models for stratified prediction of axillary lymph node metastasis in breast cancer patients (cN0)

Gào

Luo

He³

et al. 2022

Front. Endocrinol.

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ObjectivesTo determine the predictors of axillary lymph node metastasis (ALNM), two nomogram models were constructed to accurately predict the status of axillary lymph nodes (ALNs), mainly high nodal tumour burden (HNTB, > 2 positive lymph nodes), low nodal tumour burden (LNTB, 1-2 positive lymph nodes) and negative ALNM (N0). Accordingly, more appropriate treatment strategies for breast cancer patients without clinical ALNM (cN0) could be selected.MethodsFrom 2010 to 2015, a total of 6314 patients with invasive breast cancer (cN0) were diagnosed in the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and internal validation groups at a ratio of 3:1. As the external validation group, data from 503 breast cancer patients (cN0) who underwent axillary lymph node dissection (ALND) at the Second Affiliated Hospital of Chongqing Medical University between January 2011 and December 2020 were collected. The predictive factors determined by univariate and multivariate logistic regression analyses were used to construct the nomograms. Receiver operating characteristic (ROC) curves and calibration plots were used to assess the prediction models’ discrimination and calibration.ResultsUnivariate analysis and multivariate logistic regression analyses showed that tumour size, primary site, molecular subtype and grade were independent predictors of both ALNM and HNTB. Moreover, histologic type and age were independent predictors of ALNM and HNTB, respectively. Integrating these independent predictors, two nomograms were successfully developed to accurately predict the status of ALN. For nomogram 1 (prediction of ALNM), the areas under the receiver operating characteristic (ROC) curve in the training, internal validation and external validation groups were 0.715, 0.688 and 0.876, respectively. For nomogram 2 (prediction of HNTB), the areas under the ROC curve in the training, internal validation and external validation groups were 0.842, 0.823 and 0.862. The above results showed a satisfactory performance.ConclusionWe established two nomogram models to predict the status of ALNs (N0, 1-2 positive ALNs or >2 positive ALNs) for breast cancer patients (cN0). They were well verified in further internal and external groups. The nomograms can help doctors make more accurate treatment plans, and avoid unnecessary surgical trauma.

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“…Despite the use of different prognostic and predictive factors, our ability to predict breast cancer prognosis in each individual patient is limited ( 29 ). Therefore, identifying reliable and efficient prognostic factors remains a major research effort in order to avoid overtreating low-risk patients and enhance the efficacy of adjuvant treatment for those with worse prognosis.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Value of Topoisomerase 2-Alpha and B-Myb in Early Breast Cancer Treated with Adjuvant Chemotherapy

Varga

Plavetić

Podolski

et al. 2021

ACC

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Breast cancer is the most common malignancy in females. Despite its well-established prognostic factors, our prognostic ability at an individual patient level remains limited. In this study, the immunohistochemical expression of B-Myb and DNA topoisomerase 2-alpha (Topo2a) was analyzed in primary tumors to identify patients with a higher risk of disease recurrence after adjuvant chemotherapy for early invasive breast cancer. We analyzed a cohort of 215 early invasive breast cancer patients having undergone surgery from 2002 to 2003 at the Zagreb University Hospital Centre, including 153 patients treated with adjuvant chemotherapy. All of them were followed-up prospectively for at least ten years according to routine institutional practice. Statistically significant correlations were found between B-Myb and Topo2a expression levels and particular well-established prognostic factors. B-Myb expression was lower in estrogen receptor (ER)-positive tumors (p=0.0773), whereas larger tumors and those with positive lymphovascular invasion displayed a statistically significantly higher B-Myb expression (p=0.0409 and p=0.0196). Higher tumor grade indicated higher Topo2a values (p=0.0102 and p=0.0069). The subgroup with the expression of both proteins above the median value had an almost statistically significantly (p=0.0613) inferior prognosis compared to the rest of the cohort. Study results showed the B-Myb and Topo2a expression to have a prognostic value in breast cancer patients after adjuvant chemotherapy, which should be additionally explored in future studies in a larger patient cohort.

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Independent Factors for Poor Prognosis in Young Patients with Stage I-III Breast Cancer

Cited by 9 publications

References 29 publications

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Development and Validation of Prognostic Nomograms for Elderly Patients with Osteosarcoma

Nomogram models for stratified prediction of axillary lymph node metastasis in breast cancer patients (cN0)

Prognostic Value of Topoisomerase 2-Alpha and B-Myb in Early Breast Cancer Treated with Adjuvant Chemotherapy

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