Diagnosis and treatment pattern among rural and urban breast cancer patients in Southwest China from 2005 to 2009

Effect of a family-involvement combined aerobic and resistance exercise protocol on cancer-related fatigue in patients with breast cancer during postoperative chemotherapy: study protocol for a quasi-randomised controlled trial

INTRODUCTION

Cancer-related fatigue (CRF) is one of the most common and debilitating side effects experienced by patients with breast cancer (BC) during postoperative chemotherapy. Family-involvement combined aerobic and resistance exercise has been introduced as a promising non-pharmacological intervention for CRF symptom relief and improving patients' muscle strength, exercise completion, family intimacy and adaptability and quality of life. However, evidence for the practice of home participation in combined aerobic and resistance exercise for the management of CRF in patients with BC is lacking.

METHODS AND ANALYSIS

We present a protocol for a quasi-randomised controlled trial involving an 8-week intervention. Seventy patients with BC will be recruited from a tertiary care centre in China. Participants from the first oncology department will be assigned to the family-involvement combined aerobic and resistance exercise group (n=28), while participants from the second oncology department will be assigned to the control group that will receive standard exercise guidance (n=28). The primary outcome will be the Piper Fatigue Scale-Revised (R-PFS) score. The secondary outcomes will include muscle strength, exercise completion, family intimacy and adaptability and quality of life, which will be evaluated by the stand-up and sit-down chair test, grip test, exercise completion rate, Family Adaptability and Cohesion Scale, Second Edition-Chinese Version (FACESⅡ-CV) and Functional Assessment of Cancer Therapy -Breast (FACT-B) scale. Analysis of covariance will be applied for comparisons between groups, and paired t-tests will be used for comparison of data before and after exercise within a group.

ETHICS AND DISSEMINATION

This study has been approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University (PJ-KS-KY-2021-288). The results of this study will be published via peer-reviewed publications and presentations at conferences.

TRAIL REGISTRATION NUMBER

ChiCTR2200055793.

Breast Cancer Epidemiology and Survival Analysis of Shenyang in Northeast China: A Population-Based Study from 2008 to 2017

Background

To investigate the status of breast cancer incidence, trends, and survival in women in urban Shenyang from 2008–2017 using large Cancer Registry data.

Methods

Breast cancer incidence and mortality data were abstracted from the Shenyang Cancer Registry between 2008 and 2017. The crude and age-standardized incidence and mortality rates were calculated for each year. Average annual percentage changes (AAPC) were used to describe the change over time.

Results

A total of 14,255 out of 18,782,956 women were diagnosed with breast cancer between 2008 and 2017 in urban Shenyang. The overall crude and age-standardized incidences were 75.89 and 43.42 per 100,000, respectively. The crude incidence increased from 61.93 per 100,000 in 2008 to 90.07 per 100,000 in 2017, with an AAPC of 5.10%. The crude mortality increased from 11.41 per 100,000 in 2008 to 17.29 per 100,000 in 2017, with an AAPC of 4.60. The highest age-specific incidence occurs in the 55–59 year age group at a rate of 140.67 per 100,000. During the study period, 2,710 women died from breast cancer. The overall crude and age-standardized mortality rates were 14.43 and 7.43 per 100,000, respectively. The highest age-specific mortality occurs at 80–84 years old at a rate of 57.57 per 100,000. The 3-year and 5-year survival rates for female breast cancer in urban Shenyang from 2008 to 2013 were 85.61% and 77.39%, respectively, and both declined with age.

Conclusion

The incidence and mortality rates of breast cancer in Shenyang increased over time. Screening and control strategies should be enhanced, especially for perimenopausal females.

Assessing the impact of rurality on oesophagogastric cancer survival in the North-East of Scotland- a prospective population cohort study

INTRODUCTION

Despite advances in oncology therapies and surgical techniques, survival from oesophagogastric cancer remains low. Poorer cancer outcomes and survival for rural dwellers is documented worldwide and has been an area of focus in Scotland since 2007 when changes to suspected cancer national referral guidelines and governmental mandates on delivering remote and rural healthcare occurred. Whether these changes in clinical practice has impacted upon upper gastrointestinal cancer remains unclear.

METHODS

A prospective, single-centre observation study was performed. Data from the regional oesophagogastric cancer MDT between 2013 and 2019 were included. The Scottish Index of Multiple Deprivation 2020 tool provided a rurality code (1 or 2) based on patient postcode at time of referral. Survival outcomes for urban and rural patients were compared across demographic factors, disease factors and stage at presentation.

RESULTS

A total of 1038 patients were included in this study. There was no significant difference between rural and urban groups in terms of sex of patient, age at diagnosis, cancer location, or tumour stage. Furthermore, no difference was identified between those commenced on a radical therapy with other treatment plans. Despite this, rurality predicted for an improved outcome on survival analysis (p = 0.012) and this was independent of other factors on multivariable analysis (HR = 0.78, 95%CI 0.66-0.98; p = 0.032).

DISCUSSION

The difference in survival demonstrated here between urban and rural groups is not easily explained but may represent improvements to rural access to healthcare delivered as a result of Scottish Government reports.

A Retrospective Analysis of the Effect of Irinotecan-Based Regimens in Patients With Metastatic Breast Cancer Previously Treated With Anthracyclines and Taxanes

Background

At present, patients with metastatic breast cancer (MBC) have few treatment options after receiving anthracyclines and taxanes. Studies have shown that irinotecan has modest systemic activity in some patients previously treated with anthracyclines and taxanes. This study aimed to evaluate the efficacy of irinotecan-based chemotherapy for breast cancer patients in a metastatic setting.

Methods

We retrospectively collected the clinical information and survival data of 51 patients with MBC who received irinotecan at West China Hospital of Sichuan University. The primary endpoints were the progression free survival (PFS) and overall survival (OS), and the secondary endpoint was the objective response rate (ORR). To minimize potential confounding factors, we matched 51 patients who received third-line chemotherapy without irinotecan through propensity score matching (PSM) based on age, hormone receptor (HR), and human epidermal growth factor receptor 2 (HER2), compared their OS and PFS rates to those treated with irinotecan.

Results

From July 2012 to October 2020, 51 patients were treated with an irinotecan-containing regimen. The median number of previous treatment lines was 4, and a median of two previous chemotherapy cycles (ranging from 1–14 cycles) were given in a salvage line setting. The ORR was 15.7%, and the disease control rate (DCR) was 37.3%. For the irinotecan group, the median PFS was 3.2 months (95% CI 2.7–3.7), while the median OS was 33.1 months (95% CI 27.9–38.3). Univariate analysis results suggested that irinotecan could improve PFS in patients with visceral metastasis (P=0.031), which was 0.7 months longer than patients without visceral metastasis (3.5 months vs. 2.8 months). Compared to the patients who received third-line non-irinotecan chemotherapy, the irinotecan group showed a longer trend of PFS without statistical significance (3.2 months vs 2.1 months, P = 0.052). Similarly, the OS of the irinotecan group was longer than the third-line survival without irinotecan, but it was not statistically significant (33.1 months vs 18.0 months, P = 0.072).

Conclusions

For MBC patients who were previously treated with anthracyclines and/or taxanes, an irinotecan-containing regimen achieved moderate objective response and showed a trend of survival benefit, which deserves further study.

Multidimensional Machine Learning Personalized Prognostic Model in an Early Invasive Breast Cancer Population-Based Cohort in China: Algorithm Validation Study

Background

Current online prognostic prediction models for breast cancer, such as Adjuvant! Online and PREDICT, are based on specific populations. They have been well validated and widely used in the United States and Western Europe; however, several validation attempts in non-European countries have revealed suboptimal predictions.

Objective

We aimed to develop an advanced breast cancer prognosis model for disease progression, cancer-specific mortality, and all-cause mortality by integrating tumor, demographic, and treatment characteristics from a large breast cancer cohort in China.

Methods

This study was approved by the Clinical Test and Biomedical Ethics Committee of West China Hospital, Sichuan University on May 17, 2012. Data collection for this project was started in May 2017 and ended in March 2019. Data on 5293 women diagnosed with stage I to III invasive breast cancer between 2000 and 2013 were collected. Disease progression, cancer-specific mortality, all-cause mortality, and the likelihood of disease progression or death within a 5-year period were predicted. Extreme gradient boosting was used to develop the prediction model. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUROC), and the model was calibrated and compared with PREDICT.

Results

The training, test, and validation sets comprised 3276 (499 progressions, 202 breast cancer-specific deaths, and 261 all-cause deaths within 5-year follow-up), 1405 (211 progressions, 94 breast cancer-specific deaths, and 129 all-cause deaths), and 612 (109 progressions, 33 breast cancer-specific deaths, and 37 all-cause deaths) women, respectively. The AUROC values for disease progression, cancer-specific mortality, and all-cause mortality were 0.76, 0.88, and 0.82 for training set; 0.79, 0.80, and 0.83 for the test set; and 0.79, 0.84, and 0.88 for the validation set, respectively. Calibration analysis demonstrated good agreement between predicted and observed events within 5 years. Comparable AUROC and calibration results were confirmed in different age, residence status, and receptor status subgroups. Compared with PREDICT, our model showed similar AUROC and improved calibration values.

Conclusions

Our prognostic model exhibits high discrimination and good calibration. It may facilitate prognosis prediction and clinical decision making for patients with breast cancer in China.

Public health insurance and cancer-specific mortality risk among patients with breast cancer: A prospective cohort study in China

Little is known about how health insurance policies, particularly in developing countries, influence breast cancer prognosis. Here, we examined the association between individual health insurance and breast cancer-specific mortality in China. We included 7436 women diagnosed with invasive breast cancer between 2009 and 2016, at West China Hospital, Sichuan University. The health insurance plan of patient was classified as either urban or rural schemes and was also categorized as reimbursement rate (ie, the covered/total charge) below or above the median. Breast cancer-specific mortality was the primary outcome. Using Cox proportional hazards models, we calculated hazard ratios (HRs) for cancer-specific mortality, contrasting rates among patients with a rural insurance scheme or low reimbursement rate to that of those with an urban insurance scheme or high reimbursement rate, respectively. During a median follow-up of 3.1 years, we identified 326 deaths due to breast cancer. Compared to patients covered by urban insurance schemes, patients covered by rural insurance schemes had a 29% increased cancer-specific mortality (95% CI 0%-65%) after adjusting for demographics, tumor characteristics and treatment modes. Reimbursement rate below the median was associated with a 42% increased rate of cancer-specific mortality (95% CI 11%-82%). Every 10% increase in the reimbursement rate is associated with a 7% (95% CI 2%-12%) reduction in cancer-specific mortality risk, particularly in patients covered by rural insurance schemes (26%, 95% CI 9%-39%). Our findings suggest that underinsured patients face a higher risk of breast cancer-specific mortality in developing countries.

Prediction model of the response to neoadjuvant chemotherapy in breast cancers by a Naive Bayes algorithm

BACKGROUND AND OBJECTIVE

Chemotherapy is useful to many breast cancer patients, however, it is not therapeutic for some patients. Pathologic complete response (pCR) is an indicator to good response in Neoadjuvant chemotherapy (NAC). In this study, we aimed to develop a way to predict pCR before NAC.

METHODS

We retrospectively collected 287 stage II-III breast cancer cases either to a training set (N = 197) or to a test set (N = 90). Fourteen candidate genes were selected from four public microarray data sets. A prediction model was built, by using these fourteen candidate genes and three reference genes expression which were tested by TaqMan probe-based quantitative polymerase chain reaction, after selecting a better algorithm.

RESULTS

The Naive Bayes algorithm had a relatively higher predictive value, compared with random forest, support vector machine (SVM), and k-nearest neighbor (knn) algorithms (P < 0.05). This 17-gene prediction model showed a high positive correlation with pCR (odds ratio, 8.914, 95% confidence interval, 4.430-17.934, P < 0.001). By using this model, the enrolled patients were classified into sensitive (SE) and insensitive (INS) groups. The pCR rates between the SE and INS groups were highly different (42.3% vs.7.6%, P < 0.001). The sensitivity and specificity of this prediction model were 84.5% and 62.0%.

CONCLUSIONS

Instead of whole transcriptome-based technologies, panel gene expression with tens of essential genes implemented in a machine learning model has predictive potential for chemosensitivity in breast cancers.

Area socioeconomic status is independently associated with esophageal cancer mortality in Shandong, China

Esophageal cancer (EC) is a leading cause of cancer death in China. Within Shandong Province, a geographic cluster with high EC mortality has been identified, however little is known about how area-level socioeconomic status (SES) is associated with EC mortality in this province. Multilevel models were applied to EC mortality data in 2011–13 among Shandong residents aged 40+ years. Area-level SES factors consisted of residential type (urban/rural) of the sub-county-level units (n = 262) and SES index (range: 0–10) of the county-level units (n = 142). After adjustment for age and sex, residents living in rural areas had a 22% (95% CI: 13–32%) higher risk of dying from EC than those in urban areas. With each unit increase in the SES index, the average risk of dying from EC reduced by 10% (95% CI: 3–18%). The adjustment of area-level SES variables had little impact on the risk ratio of EC mortality between the high-mortality cluster and the rest of Shandong. In conclusion, rural residence and lower SES index are strongly associated with elevated risks of EC death. However, these factors are independent of the high mortality in the cluster area of Shandong. The underlying causes for this geographic disparity need to be further investigated.

Predicting Invasive Disease-Free Survival for Early-stage Breast Cancer Patients Using Follow-up Clinical Data

OBJECTIVE

Chinese women are seriously threatened by breast cancer with high morbidity and mortality. The lack of robust prognosis models results in difficulty for doctors to prepare an appropriate treatment plan that may prolong patient survival time. An alternative prognosis model framework to predict Invasive Disease-Free Survival (iDFS) for early-stage breast cancer patients, called MP4Ei, is proposed. MP4Ei framework gives an excellent performance to predict the relapse or metastasis breast cancer of Chinese patients in 5 years.

METHODS

MP4Ei is built based on statistical theory and gradient boosting decision tree framework. 5246 patients, derived from the Clinical Research Center for Breast (CRCB) in West China Hospital of Sichuan University, with early-stage (stage I-III) breast cancer are eligible for inclusion. Stratified feature selection, including statistical and ensemble methods, is adopted to select 23 out of the 89 patient features about the patient' demographics, diagnosis, pathology and therapy. Then 23 selected features as the input variables are imported into the XGBoost algorithm, with Bayesian parameter tuning and cross validation, to find out the optimum simplified model for 5-year iDFS prediction.

RESULTS

For eligible data, with 4196 patients (80%) for training, and with 1050 patients (20%) for testing, MP4Ei achieves comparable accuracy with AUC 0.8451, which has a significant advantage (p < 0.05).

CONCLUSION

This work demonstrates the complete iDFS prognosis model with very competitive performance.

SIGNIFICANCE

The proposed method in this paper could be used in clinical practice to predict patients' prognosis and future surviving state, which may help doctors make treatment plan.

Rural dwellers are less likely to survive cancer - An international review and meta-analysis

BACKGROUND

Existing research from several countries has suggested that rural-dwellers may have poorer cancer survival than urban-dwellers. However, to date, the global literature has not been systematically reviewed to determine whether a rural cancer survival disadvantage is a global phenomenon.

METHODS

Medline, CINAHL, and EMBASE were searched for studies comparing rural and urban cancer survival. At least two authors independently screened and selected studies. We included epidemiological studies comparing cancer survival between urban and rural residents (however defined) that also took socioeconomic status into account. A meta-analysis was conducted using 11 studies with binary rural:urban classifications to determine the magnitude and direction of the association between rurality and differences in cancer survival. The mechanisms for urban-rural cancer survival differences reported were narratively synthesised in all 39 studies.

FINDINGS

39 studies were included in this review. All were retrospective observational studies conducted in developed countries. Rural-dwellers were significantly more likely to die when they developed cancer compared to urban-dwellers (HR 1.05 (95% CI 1.02 - 1.07). Potential mechanisms were aggregated into an ecological model under the following themes: Patient Level Characteristics; Institutions; Community, Culture and Environment; Policy and Service Organization.

INTERPRETATION

Rural residents were 5% less likely to survive cancer. This effect was consistently observed across studies conducted in various geographical regions and using multiple definitions of rurality. High quality mixed-methods research is required to comprehensively evaluate the underlying factors. We have proposed an ecological model to provide a coherent framework for future explanatory research.

FUNDING

None.

Surgery of the primary tumor improves survival in women with stage IV breast cancer in Southwest China: A retrospective analysis

The International Consensus Guidelines for advanced breast cancer (ABC) considers that the surgery of the primary tumor for stage IV breast cancer patients does not usually improve the survival. However, studies have showed that resection of the primary tumor may benefit these patients. The correlation between surgery and survival remains unclear.The impact of surgery and other clinical factors on overall survival (OS) of stage IV patients is investigated in West China Hospital. Female patients diagnosed with stage IV breast cancer between 1999 and 2014 were included (N = 223). Univariate and multivariate analysis assessed the association between surgery and OS.One hundred seventy-seven (79.4%) underwent surgery for the primary tumor, and 46 (20.6%) had no surgery. No significant differences were observed in age at diagnosis, T-stage, N-stage, histological grade, molecular subtype, hormone receptor (HR), and number of metastatic sites between 2 groups. Patients in the surgery group had dramatically longer OS (45.6 vs 21.3 months, log-rank P < .001). In univariate analysis, survival was associated with surgical treatment, residence, tumor size, lymph node, HR status, hormonal therapy, and radiotherapy. In multivariate analysis, surgery was an independent prognostic factor for OS [hazard ratio (HR), 0.569; 95% confidence interval (CI) 0.329-0.984, P = .044]. Additional independent prognostic factors were hormonal therapy (HR, 0.490; 95% CI 0.300-0.800) and radiotherapy (HR, 0.490; 95% CI 0.293-0.819). In addition, a favorable impact of surgery was observed by subgroup analysis.Our study showed that surgery of the primary breast tumor has a positive impact on OS in with stage IV breast cancer patients.