Patterns of metastasis and prognosis of elderly esophageal squamous cell carcinoma patients in stage IVB: a population-based study

Effects of Local Treatment in Combination with Systemic Therapy for Advanced Esophageal Cancer: A Systematic Review and Meta-analysis

Purpose

Initial studies investigating the combination of local and systemic treatments in advanced esophageal cancer (EC) have conflicting conclusions regarding survival benefits. The objective of this systematic review and meta-analysis is to assess the efficacy of the addition of local therapy to systemic treatments in patients with advanced EC.

Methods and Materials

A systematic literature search was conducted in the PubMed, EMBASE, and CENTRAL databases. Key eligibility criteria included studies that enrolled patients with histologically confirmed EC or esophagogastric junction cancer with metastasis or recurrence and compared survival benefits between the combined local and systemic treatment group and the systemic treatment alone group. Survival outcomes, represented by hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS), were pooled using a random effects model. The MINORS score was adopted for quality assessment. Risk of bias was statistically examined by Begg's and Egger's tests.

Results

A total of 1 randomized controlled trial (RCT) and 10 qualified retrospective studies including 14,489 patients were identified. Addition of local therapy to systemic treatment significantly improved PFS (HR, 0.52; 95% CI, 0.37-0.73; P < .001) and OS (HR, 0.69; 95% CI, 0.58-0.81; P < .0001) compared with systemic treatment alone. The subgroup analysis revealed that combined local and systemic treatment conferred a significant survival advantage in both patients with oligometastasis (PFS: HR, 0.45; 95% CI, 0.31-0.64; P < .0001; OS: HR, 0.62; 95% CI, 0.48-0.79; P < .0001) and recurrence (OS: HR, 0.55; 95% CI, 0.37-0.81; P = .002).

Conclusions

In conclusion, addition of local treatment to systemic therapy can improve survival in patients with advanced EC, particularly in those with oligometastasis or recurrent diseases.

Patterns of distant metastasis and survival outcomes in de novo metastatic breast cancer according to age groups

Background

Is de novo metastatic breast cancer (dnMBC) the same disease in the elderly as in younger breast cancer remains unclear. This study aimed to determine the metastatic patterns and survival outcomes in dnMBC according to age groups.

Methods

We included patients from the Surveillance Epidemiology and End Results program. Chi-square test, multivariate logistic regression analyses, and multivariate Cox regression models were used for statistical analyses.

Results

A total of 17719 patients were included. There were 3.6% (n=638), 18.6% (n=3290), 38.0% (n=6725), and 39.9% (n=7066) of patients aged <35, 35-49, 50-64, and ≥65 years, respectively. Older patients had a significantly higher risk of lung metastasis and a significantly lower risk of liver metastasis. There were 19.1%, 25.6%, 30.9%, and 35.7% of patients with lung metastasis in those aged <35, 35-49, 50-64, and ≥65 years, respectively. Moreover, the proportion of liver metastasis was 37.6%, 29.5%, 26.3%, and 19.2%, respectively. Age was the independent prognostic factor associated with breast cancer-specific survival (BCSS) and overall survival (OS). Those aged 50-64 years had significantly inferior BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. Patients aged ≥65 years also had significantly lower BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. However, similar outcomes were found between those aged 35-49 and <35 years.

Conclusion

Our study suggests that different age groups may affect the metastatic patterns among patients with dnMBC and the survival of younger patients is more favorable than those of older patients.

Advanced esophageal cancer with bone metastases: Prognostic biomarkers and palliative treatment

Esophageal cancer (EC) is a common and devastating tumor of the upper digestive tract. Unfortunately, by the time any symptoms have manifested, the disease has often progressed to an advanced stage and is accompanied by macro- and micrometastases, including in the bones. The treatment of esophageal cancer with bone metastases remains clinically challenging, given the poor prognosis associated with this condition. Effective prognostic biomarkers can help medical staff choose the appropriate operation and treatment plan, that is for most beneficial for making patients. Current treatments for esophageal cancer with bone metastases include pain-relieving drugs, surgical therapy, radiotherapy (RT), chemotherapy (CT, including molecular-targeted drug therapy), endocrine therapy (ET), bisphosphonates (BPs) and interventional therapy. Of these robust measures, radiotherapy has emerged as a particularly promising therapy for bone metastases from esophageal cancer. Substantial progress has been made in radiation therapy techniques since the discovery of X-rays by Roentgen in 1895. In its palliative capacity, the key goals of radiotherapy are to relieve the patients' bone pain and debilitate effects, including relieving spinal cord compression, correcting the spinal deformity and restoring spinal stability. However, it is worth mentioning that RT for esophageal cancer has various side effects. Currently, the available studies focused exclusively on radiotherapy for ECBM are too small to draw any definitive conclusions, and each of these studies has significant limitations. In this review, in addition to the epidemiology described at the beginning, we will explore the current prognostic biomarkers and radiotherapy for esophageal cancer, with a particular focus on those with bone metastases.

Individualized treatment decision model for inoperable elderly esophageal squamous cell carcinoma based on multi-modal data fusion

BACKGROUND

This research aimed to develop a model for individualized treatment decision-making in inoperable elderly patients with esophageal squamous cell carcinoma (ESCC) using machine learning methods and multi-modal data.

METHODS

A total of 189 inoperable elderly ESCC patients aged 65 or older who underwent concurrent chemoradiotherapy (CCRT) or radiotherapy (RT) were included. Multi-task learning models were created using machine learning techniques to analyze multi-modal data, including pre-treatment CT images, clinical information, and blood test results. Nomograms were constructed to predict the objective response rate (ORR) and progression-free survival (PFS) for different treatment strategies. Optimal treatment plans were recommended based on the nomograms. Patients were stratified into high-risk and low-risk groups using the nomograms, and survival analysis was performed using Kaplan-Meier curves.

RESULTS

The identified risk factors influencing ORR were histologic grade (HG), T stage and three radiomic features including original shape elongation, first-order skewness and original shape flatness, while risk factors influencing PFS included BMI, HG and three radiomic features including high gray-level run emphasis, first-order minimum and first-order skewness. These risk factors were incorporated into the nomograms as independent predictive factors. PFS was substantially different between the low-risk group (total score ≤ 110) and the high-risk group (total score > 110) according to Kaplan-Meier curves (P < 0.05).

CONCLUSIONS

The developed predictive models for ORR and PFS in inoperable elderly ESCC patients provide valuable insights for predicting treatment efficacy and prognosis. The nomograms enable personalized treatment decision-making and can guide optimal treatment plans for inoperable elderly ESCC patients.

Surgical Outcome and Prognosis of Patients with Spinal Metastasis from Esophageal Cancer: The Experience from a Single Center

BACKGROUND

The spine is one of the common sites of esophageal cancer metastasis, with a worse prognosis than that of metastasis occurring in other sites. However, the exact mechanism underlying metastatic spinal esophageal cancer (MSEC) is poorly understood possibly due to the short survival time of patients. The aim of this study was to evaluate surgical outcomes and factors affecting the prognosis of patients with MSEC.

METHODS

Enrolled in this retrospective study were 20 consecutive patients who received surgical treatment for MSEC in our hospital from 2013 to 2020. The impact of surgery on patient's quality of life was assessed by visual analog scale score and American Spinal Injury Association grade. Prognostic variables relative to traditional clinical parameters and inflammation and nutrition indicators were identified by univariate and multivariate analyses.

RESULTS

The median survival time of patients with MSEC was 6 months, with a one-year survival rate of 20%. Pain relief was achieved in most patients, and nerve function was recovered in part of the patients after surgery. Analysis of clinical factors showed that total tumor resection was beneficial to overall survival of patients with MSEC. Laboratory indicators of erythrocyte sedimentation rate, neutrophil/lymphocyte ratio, and platelet/lymphocyte ratio were identified as independent prognostic factors for patients with MSEC.

CONCLUSIONS

Timely surgical intervention can improve the quality of life of patients with MSEC. The preoperative erythrocyte sedimentation rate, neutrophil/lymphocyte ratio, and platelet/lymphocyte ratio could help predict the overall survival of patients with MSEC. These findings may help in decision-making for the treatment of patients with MSEC.

A Nomogram Model to Predict Post-Progression Survival in Esophageal Squamous Cell Carcinoma Patients With Recurrence After Radical Resection

Background

Esophageal squamous cell carcinoma (ESCC) is characterized clinically by frequent recurrence, leading to a poor prognosis after radical surgery. The aim of this study was to identify a prognostic nomogram to predict the post-progression survival (PPS) of ESCC patients based on the features of primary tumor and recurrence.

Methods

A total of 234 ESCC patients who underwent recurrence after radical surgery were enrolled in this study. The independent prognostic factors screened by the univariate and multivariate Cox regression analysis were subsequently used to construct a nomogram. The predictive performance of the nomogram was evaluated with the concordance index (C-index), decision curve, and the area under the receiver operating characteristic curve (AUC) and validated in two validation cohorts. The Kaplan-Meier curves of different recurrence patterns were analyzed.

Results

The prognostic nomogram of PPS was established by integrating independent prognostic factors, including age, body mass index, number of lymph node dissection, recurrence pattern, and recurrence treatment. The nomogram demonstrated good performance, with C-index values of 0.756, 0.817, and 0.730 for the training and two validation cohorts. The 1-year AUC values were 0.773, 0.798, and 0.735 and 3-year AUC values were 0.832, 0.871, and 0.791, respectively. Furthermore, we found that patients with bone metastasis displayed the worst PPS compared to other isolated recurrence patterns.

Conclusion

We constructed a nomogram to reliably predict PPS, which would be valuable to provide individual managements for ESCC patients after radical surgery.