Effect of adjuvant chemotherapy on the survival outcomes of elderly breast cancer: A retrospective cohort study based on SEER database

Geriatric Breast Cancer: Staging, Molecular Surrogates, and Treatment. A Review & Meta-analysis

Breast cancer (BC) is one of the most frequent cancers in females across the globe. Treatment recommendations for BC patients are primarily driven by patient age, staging and tumor molecular subtype. Thus, we updated the general overview of BC staging, molecular surrogates, and treatment choices for women >70 years based on a systematic study encompassing the years 2013-2023. A PRISMA guidelines and PICO framework were followed, and relevant research articles were searched using different data bases (Web of Sciences, PubMed, MEDLINE, and Scopus). Mixed Methods Appraisal Tool was used for studies quality assessment. The research articles that made it into the systematic review were compiled using qualitative criteria. In the meanwhile, heterogeneity was determined using meta-analysis with RevMan 5.4. We applied a random effects model with a 0.05 significance level. Overall, there were 4151 research articles, after screening only 17 articles with 39,906 patients were included. Conclusion: Elderly patients with breast cancer should be treated differently in an adapted way. The treatment should not be the same worldwide due to different health systems. Molecular surrogates are different in geriatric patients. Surgery is the best option for treatment in this subset of patients. We need to have therapeutic decision appointments for elderly patients with breast cancer. The guidelines and medical authority should be used in the best decision.

Screening of postoperative adjuvant chemotherapy-related serum metabolic markers in breast cancer patients based on 1H NMR metabonomics

Background

Breast cancer (BC) has the highest incidence rate among female malignant tumors. Adjuvant chemotherapy is commonly used to reduce micrometastasis in postoperative patients. However, monitoring the efficacy of chemotherapy in BC is a major challenge in clinical practice. In this study, 1H nuclear magnetic resonance (NMR) metabonomics was performed to explore the serum metabolic characteristics of BC patients before and after adjuvant chemotherapy.

Methods

In this study, we collected serum samples from 51 healthy controls and 61 BC patients before and after chemotherapy for 1H NMR metabolomic analysis, and tested the performance of each metabolite and combination segment by the receiver operating characteristic (ROC) curves.

Results

Nine metabolites, namely glutamine, citrate, creatine, glycerophosphatidylcholine/phosphatidylcholine, glycine, 1-methylhistidine, lactate, pyruvate and formate had significant changes in BC patients before chemotherapy compared with healthy controls. Lactate, pyruvate, 1-methylhistidine and formate were found to be inversely regulated by chemotherapy. ROC analysis showed that a combination of the four metabolites had good prediction for chemotherapy efficacy with area under the curve of 0.958, sensitivity of 98.36% and specificity of 91.30%. There was no significant correlation between chemotherapy-related metabolites and clinical indicators of cancer patients, indicating that they can be used to evaluate the chemotherapy efficacy of patients with different clinical indicators.

Conclusions

Effectively, dynamic and non-invasive metabolic markers for the evaluation of the efficacy of chemotherapy were identified in this study.

Deep learning-guided adjuvant chemotherapy selection for elderly patients with breast cancer

PURPOSE

The efficacy of adjuvant chemotherapy in elderly breast cancer patients is currently controversial. This study aims to provide personalized adjuvant chemotherapy recommendations using deep learning (DL).

METHODS

Six models with various causal inference approaches were trained to make individualized chemotherapy recommendations. Patients who received actual treatment recommended by DL models were compared with those who did not. Inverse probability treatment weighting (IPTW) was used to reduce bias. Linear regression, IPTW-adjusted risk difference (RD), and SurvSHAP(t) were used to interpret the best model.

RESULTS

A total of 5352 elderly breast cancer patients were included. The median (interquartile range) follow-up time was 52 (30-80) months. Among all models, the balanced individual treatment effect for survival data (BITES) performed best. Treatment according to following BITES recommendations was associated with survival benefit, with a multivariate hazard ratio (HR) of 0.78 (95% confidence interval (CI): 0.64-0.94), IPTW-adjusted HR of 0.74 (95% CI: 0.59-0.93), RD of 12.40% (95% CI: 8.01-16.90%), IPTW-adjusted RD of 11.50% (95% CI: 7.16-15.80%), difference in restricted mean survival time (dRMST) of 12.44 (95% CI: 8.28-16.60) months, IPTW-adjusted dRMST of 7.81 (95% CI: 2.93-11.93) months, and p value of the IPTW-adjusted Log-rank test of 0.033. By interpreting BITES, the debiased impact of patient characteristics on adjuvant chemotherapy was quantified, which mainly included breast cancer subtype, tumor size, number of positive lymph nodes, TNM stages, histological grades, and surgical type.

CONCLUSION

Our results emphasize the potential of DL models in guiding adjuvant chemotherapy decisions for elderly breast cancer patients.

Prognostic nomograms for breast cancer with lung metastasis: a SEER-based population study

BACKGROUND

Lung metastasis is a significant adverse predictor of prognosis in patients with breast cancer. Accurate estimation for the prognosis of patients with lung metastasis and population-based validation for the models are lacking. In the present study, we aimed to establish the nomogram to identify prognostic factors correlated with lung metastases and evaluate individualized survival in patients with lung metastasis based on SEER (Surveillance, Epidemiology, and End Results) database.

METHODS

We selected 1197 patients diagnosed with breast cancer with lung metastasis (BCLM) from the SEER database and randomly assigned them to the training group (n = 837) and the testing group (n = 360). Based on univariate and multivariate Cox regression analysis, we evaluated the effects of multiple variables on survival in the training group and constructed a nomogram to predict the 1-, 2-, and 3-year survival probability of patients. The nomogram were verified internally and externally by Concordance index (C-index), Net Reclassification (NRI), Integrated Discrimination Improvement (IDI), Decision Curve Analysis (DCA), and calibration plots.

RESULTS

According to the results of multi-factor Cox regression analysis, age, histopathology, grade, marital status, bone metastasis, brain metastasis, liver metastasis, human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR), surgery, neoadjuvant therapy and chemotherapy were considered as independent prognostic factors for patients with BCLM. The C-index in the training group was 0.719 and the testing group was 0.695, respectively. The AUC values of the 1-, 2-, and 3-year prognostic nomogram in the training group were 0.798, 0.790 and 0.793, and the corresponding AUC values in the testing group were 0.765, 0.761 and 0.722. The calculation results of IDI and NRI were shown. The nomograms significantly improved the risk reclassification for 1-, 2-, and 3-year overall mortality prediction compared with the AJCC 7th staging system. According to the calibration plot, nomograms showed good consistency between predicted and actual overall survival (OS) values for the patients with BCLM. DCA showed that nomograms had better net benefits at different threshold probabilities at different time points compared with the AJCC 7th staging system.

CONCLUSIONS

Nomograms that predicted 1-, 2-, and 3-year OS for patients with BCLM were successfully constructed and validated to help physicians in evaluating the high risk of mortality in breast cancer patients.

Non-pegylated liposomal doxorubicin in older adjuvant early breast cancer patients: cardiac safety analysis and final results of the COLTONE study

AIMS

To explore the cardiac safety of adjuvant Non-Pegylated Liposomal Doxorubicin (NPL-DOX) plus Cyclophosphamide (CTX) followed by weekly Paclitaxel, in elderly women (≥ 65 years) with high-risk breast cancer. Previously, we described no symptomatic cardiac events within the first 12 months from starting treatment. We now reported the updated results after a median follow-up 76 months.

METHODS

The cardiac activity was evaluated with left ventricular ejection fraction (LVEF) echocardiograms assessments, before starting chemotherapy and every 6 months, until 30 months from baseline, then yearly for at least 5 years.

RESULTS

Forty-seven women were recruited by two Units of Medical Oncology (Ethics Committee authorization CESM-AOUP, 3203/2011; EudraCT identification number: 2010-024067-41, for Pisa and Pontedera Hospitals). An episode of grade 3 CHF (NCI-CTCAE, version 3.0) occurred after 18 months the beginning of chemotherapy. The echocardiograms assessments were performed comparing the LVEF values of each patient evaluated at fixed period of time, compared to baseline. We observed a slight changed in terms of mean values at 48, 60, 72 and 84 months. At these time points, a statistically significant reduction of - 3.2%, - 4.6%, - 6.4% and - 7.1%, respectively, was observed. However, LVEF remained above 50% without translation in any relevant clinical signs. No other cardiac significant episodes were reported. To this analysis, in 13 patients (28%) occurred disease relapse and,  of them, 11 (23%) died due to metastatic disease. Eight patients died of cancer-unrelated causes.

CONCLUSIONS

The combination including NPL-DOX in elderly patients revealed low rate of cardiac toxic effects. Comparative trials are encouraged.