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

Temporal trends of breast cancer burden in the Western Pacific Region from 1990 to 2044: Implications from the Global Burden of Disease Study 2019

INTRODUCTION

Breast cancer (BC) is a malignant disease that occurs worldwide and poses serious health burden.

OBJECTIVES

To assess the prevalence of BC burden in the Western Pacific region (WPR) from 1990 to 2019, and to predict trends from 2020 to 2044. To analyze the driving factors and put forward the region-oriented improvement.

METHODS

Based on the Global Burden of Disease Study 2019, BC cases, deaths, disability-adjusted life years (DALYs) cases, age-standardized incidence rate (ASIR), age-standardized death rate (ASDR), and age-standardized DALYs rate in WPR from 1990 to 2019 was obtained and analysed. Age-period-cohort (APC) model was used to analyze age, period, and cohort effects in BC, and Bayesian APC (BAPC) was used to predict trends over the next 25 years.

RESULTS

In conclusion, BC incidence and deaths in the WPR have increased rapidly over the past 30 years and are expected to continue to increase between 2020 and 2044. Among behavioral and metabolic factors, high body-mass index was the main risk factor for BC mortality in middle-income countries, whereas alcohol use was the main risk factor in Japan. Age is a key factor in the development of BC, with 40 years being the critical point. Incidence trends coincide with the course of economic development.

CONCLUSIONS

The BC burden remains an essential public health issue in the WPR and will increase substantially in the future. More efforts should be made in middle-income countries to prompt the health behavior and minimize the burden of BC because these nations accounts for the majority of BC burden in the WPR.

How the National Health Insurance Coverage policy changed the use of lenvatinib for adult patients with advanced hepatocellular carcinoma: a retrospective cohort analysis with real world big data

BACKGROUND

To establish a long-term mechanism to control the cost burden of drugs, the Chinese government organized seven rounds of price negotiations for the national reimbursement drug list (NRDL) from 2016 to the end of 2022. The study aimed to evaluate the impact of the National Health Insurance Coverage (NHIC) policy on the use of lenvatinib as the first-line treatment for advanced hepatocellular carcinoma (HCC) within a specific medical insurance region from the micro perspective of individual patient characteristics.

METHODS

The data of HCC patients that received lenvatinib from September 2019 to August 2022 was retrieved from the Medical and Health Big Data Center and longitudinally analyzed. Contingency table chi-square statistics and binary logistic regression analysis were used to compare the differences in the categorical variables. Interrupted time-series (ITS) regression analysis was performed to evaluate the changes in the utilization of lenvatinib over 36 months. Multiple linear regression was used to analyze the impact of receiving lenvatinib on the total hospitalization expenses of hospitalized patients with advanced HCC.

RESULTS

A total of 12,659 patients with advanced HCC were included in this study. The usage rate of lenvatinib increased from 6.19% to 15.28% over 36 months (P < 0.001). By controlling the other factors, consistent with this, the probability of patients with advanced HCC receiving lenvatinib increased by 2.72-fold after the implementation of the NHIC policy (OR = 2.720, 95% CI:2.396-3.088, P < 0.001). Older, residency in rural areas, lack of fixed income, treatment at hospitals below the tertiary level, and coverage by urban-rural residents' basic medical insurance (URRBMI) were the factors affecting the use of lenvatinib among patients with advanced HCC (P < 0.05). After the implementation of the NHIC policy, the total hospitalization expenses increased (Beta=-0.040, P < 0.001). However, compared to patients who received lenvatinib, the total hospitalization expenses were higher for those who did not receive the drug (US$5022.07 ± US$5488.70 vs. US$3701.63 ± US$4330.70, Beta = 0.062, P < 0.001).

CONCLUSIONS

The NHIC policy has significantly increased the utilization of lenvatinib. In addition, we speculate that establishing multi-level medical insurance systems for economically disadvantaged patients would be beneficial in improving the effectiveness of the NHIC policy in the real world.

The impact of insurance status on in-hospital mortality in patients with hyperglycaemic crisis: A propensity score matching analysis

AIM

This study was designed to determine the associations between insurance status and clinical outcomes among patients with hyperglycaemic crisis.

METHODS

Overall, 1668 patients with hyperglycaemic crisis were recruited from the Chongqing Medical University Medical Data Science Academy's big data platform. In-hospital mortality, length of stay and complications (i.e., hypoglycaemia, hypokalemia, pulmonary infection, multiple systemic organ failure, acute kidney injury and deep venous thrombosis) were assessed. Propensity score matching analysis was used to reduce the confounding bias, and univariate and multivariate logistic regression were used to estimate the effect of insurance status on mortality in patients with hyperglycaemic crisis.

RESULTS

After matching one uninsured patient to two insured patients with a calliper of 0.02, the uninsured group suffered a higher burden of in-hospital mortality than the insured group (16.9% vs. 9.8%); the insured status (odds ratio = 0.216, 95% confidence interval = 0.079-0.587) was a potential protect factor for in-hospital mortality of patients with hyperglycaemic crisis in the multivariate logistic regression analysis.

CONCLUSIONS

Insurance status is associated with the outcomes of hospitalisation for hyperglycaemic crisis; uninsured patients with hyperglycaemic crisis face a higher risk of mortality in China.

TRIM21 mediates the synergistic effect of Olaparib and Sorafenib by degrading BRCA1 through ubiquitination in TNBC

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive type of breast cancer with a poor prognosis and a high recurrence rate. Chemotherapy is still the mainstay of treatment for cancer patients without a genetic BRCA mutation, despite the approval of Olaparib, an inhibitor of the poly (ADP-ribose) polymerase (PARP) enzyme. Tripartite motif containing-21 (TRIM21) is one of the TRIM family members that has been investigated in various types of cancer. Here, we found that a low TRIM21 expression level was correlated with poor overall survival of TNBC patients. Knockout of TRIM21 promoted the proliferation of TNBC cells in vivo and in vitro, as well as migratory and invasive capabilities in vitro. Importantly, breast cancer susceptibility gene 1 (BRCA1) was identified as a ubiquitination substrate of TRIM21. It was confirmed that BRCA1 was upregulated after Olaparib treatment, which may explain the relative resistance of BRCA1-proficient TNBC cells to Olaparib. Moreover, Sorafenib, a standard treatment for hepatocellular carcinoma, increased the sensitivity of TNBC cells to Olaparib by promoting TRIM21-mediated ubiquitination degradation of BRCA1. Thus, a synergic effect of Olaparib and Sorafenib was found in vitro and in vivo. This combined treatment also aggravated DNA damage, cell cycle arrest, and apoptosis of TNBC cells. In summary, the findings verified the synergistic effect of Olaparib and Sorafenib and revealed TRIM21 as a potential target for TNBC therapy.

Insurance status impacts survival of hepatocellular carcinoma patients after liver resection

BACKGROUND

This study intends to examine the effect of public insurance status on survival outcomes of HCC patients after liver resection in China.

METHODS

We divided 2911 HCC patients after liver resection included in our study into the Urban Employed-based Medical Insurance group (UEBMI group, n = 1462) and the non-Urban Employed-based Medical Insurance group (non-UEBMI group, n = 1449). A propensity score matching (PSM) analysis was used to control confounding factors. Overall survival (OS) was estimated by Kaplan-Meier curves and Cox proportional hazard models based on variables screened by Lasso regression. Competing risk analysis was used to analyze cancer-specific survival (CSS).

RESULTS

UEBMI group had more male patients (p = 0.031), patients in the UEBMI group were older (p < 0.001) and had lower Charlson Comorbidity Index scores (CCI score, p < 0.001). Meanwhile, patients in the UEBMI group had better liver function (albumin-bilirubin grade I [ALBI I], p < 0.001) and lower tumor burden (α-fetoprotein [AFP], p = 0.009; Barcelona Clinic Liver Cancer stage [BCLC], p = 0.026; Milan criteria, p < 0.001; tumor size, p < 0.001; microvascular invasion [MVI], p = 0.030; portal vein tumor thrombosis [PVTT], p = 0.002). More patients in the UEBMI group received laparoscopic surgery (p = 0.024) and adjuvant transarterial chemoembolization (TACE, p < 0.001). After PSM, patients in the two matched groups had similar characteristics. Patients with recurrent HCC in the UEBMI were more likely to receive curative therapy (p < 0.001) and less likely to receive supportive care (p < 0.001). HCC patients after liver resection in the non-UEBMI group had a worse OS before (p < 0.0001) and after PSM (p = 0.002). [Correction added on August 16, 2023 after first online publication. The p value has been updated in the preceding sentence.] In our Lasso-Cox risk regression model, public health insurance status was an independent factor linked with OS (non-UEBMI vs. UEBMI, hazard ratio [HR]: 1.27; 95% confidence interval [CI]: 1.12-1.46; p < 0.001). In the competing risk analysis, patients in the UEBMI group had a lower cumulative incidence of CSS before (p < 0.001) and after PSM (p = 0.001), and public insurance status of HCC patients after liver resection remained independently associated with CSS (non-UEBMI vs. UEBMI; HR:1.36; 95% CI: 1.18-1.58; p < 0.001).

CONCLUSIONS

Underinsured HCC patients after liver resection had worse survival outcomes. Less access to care for underinsured patients may explain the difference in survival, but the corresponding conclusions need to be further explored.

Association of public health insurance with cancer-specific mortality risk among patients with nasopharyngeal carcinoma: a prospective cohort study in China

Objective

Health insurance programs are effective in preventing financial hardship in patients with cancer. However, not much is known about how health insurance policies, especially in Southwest China with a high incidence of nasopharyngeal carcinoma (NPC), influence patients' prognosis. Here, we investigated the association of NPC-specific mortality with health insurance types and self-paying rate, and the joint effect of insurance types and self-paying rate.

Materials and methods

This prospective cohort study was conducted at a regional medical center for cancer in Southwest China and included 1,635 patients with pathologically confirmed NPC from 2017 to 2019. All patients were followed up until May 31, 2022. We determine the cumulative hazard ratio of all-cause and NPC-specific mortality in the groups of various insurance kinds and the self-paying rate using Cox proportional hazard.

Results

During a median follow-up period of 3.7 years, 249 deaths were recorded, of which 195 deaths were due to NPC. Higher self-paying rate were associated with a 46.6% reduced risk of NPC-specific mortality compared to patients with insufficient self-paying rate (HR: 0.534, 95% CI: 0.339-0.839, p = 0.007). For patients covered by Urban and Rural Residents Basic Medical Insurance (URRMBI), and for patients covered by Urban Employee Basic Medical Insurance, each 10% increase in the self-paying rate reduced the probability of NPC-specific death by 28.3 and 25%, respectively (UEBMI).

Conclusion

Results of this study showed that, despite China's medical security administration improved health insurance coverage, NPC patients need to afford the high out-of-pocket medical costs in order to prolong their survival time.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

Application of serum SERS technology based on thermally annealed silver nanoparticle composite substrate in breast cancer

Liquid biopsy is currently a non-destructive and convenient method of cancer screening, due to human blood containing a variety of cancer-related biomolecules. Therefore, the development of an accurate and rapid breast cancer screening technique combined with breast cancer serum is crucial for the treatment and prognosis of breast cancer patients. In this study, the surface enhanced Raman spectroscopy (SERS) technique is used to enhance the Raman spectroscopy (RS) signal of serum based on a high sensitivity thermally annealed silver nanoparticle/porous silicon bragg mirror (AgNPs/PSB) composite substrate. Compared with RS, SERS reflects more and stronger spectral peak information, which is beneficial to discover new biomarkers of breast cancer. At the same time, to further explore the diagnostic ability of SERS technology for breast cancer. In this study, the raw spectral data are processed by baseline correction, polynomial smoothing, and normalization. Then, the relevant feature information of SERS and RS is extracted by principal component analysis (PCA), and five classification models are established to compare the diagnostic performance of SERS and RS models respectively. The experimental results show that the breast cancer diagnosis model based on the improved SERS substrate combined with the machine learning algorithm can be used to distinguish breast cancer patients from controls. The accuracy, sensitivity, specificity and AUC values of the SVM model are 100%, 100%, 100% and 100%, respectively, as well as the training time of 4ms. The above experimental results show that the SERS technology based on AgNPs/PSB composite substrate, combined with machine learning methods, has great potential in the rapid and accurate identification of breast cancer patients.

Mammography radiomics features at diagnosis and progression-free survival among patients with breast cancer

BACKGROUND

The associations between mammographic radiomics and breast cancer clinical endpoints are unclear. We aimed to identify mammographic radiomics features associated with breast cancer prognosis.

METHODS

Nested from a large breast cancer cohort in our institution, we conducted an extreme case-control study consisting of 207 cases with any invasive disease-free survival (iDFS) endpoint <5 years and 207 molecular subtype-matched controls with >5-year iDFS. A total of 632 radiomics features in craniocaudal (CC) and mediolateral oblique (MLO) views were extracted from pre-treatment mammography. Logistic regression was used to identify iDFS-associated features with multiple testing corrections (Benjamini-Hochberg method). In a subsample with RNA-seq data (n = 96), gene set enrichment analysis was employed to identify pathways associated with lead features.

RESULTS

We identified 15 iDFS-associated features from CC-view yet none from MLO-view. S(1,-1)SumAverg and WavEnLL_s-6 were the lead ones and associated with favourable (OR 0.64, 95% CI 0.42-0.87, P = 0.01) and poor iDFS (OR 1.53, 95% CI 1.31-1.76, P = 0.01), respectively. Both features were associated with eight pathways (primarily involving cell cycle regulation) in tumour but not adjacent normal tissues.

CONCLUSION

Our findings suggest mammographic radiomics features are associated with breast cancer iDFS, potentially through pathways involving cell cycle regulation.

Burden, trends, and risk factors for breast cancer in China from 1990 to 2019 and its predictions until 2034: an up-to-date overview and comparison with those in Japan and South Korea

BACKGROUND

The difference in epidemiological characteristics of breast cancer (BC) across countries is valuable for BC management and prevention. The study evaluated the up-to-date burden, trends, and risk factors of BC in China, Japan and South Korea during 1990-2019 and predicted the BC burden until 2034.

METHODS

Data on incident cases, deaths, disability-adjusted life-years (DALYs) and age-standardized rate (ASR) of BC were extracted from the Global Burden of Disease Study 2019. Trend analysis and prediction until 2034 were conducted by estimated annual percentage change and a Bayesian age-period-cohort model, respectively. Besides, the attributable burden to BC risk factors was also estimated.

RESULTS

In 2019, the number of BC incident cases, deaths and DALYs in China were 375,484, 96,306 and 2,957,453, respectively. The ASR of incidence increased, while that of death and DALYs decreased for Chinese females and Japanese and South Korean males during 1990-2019. High body-mass-index (BMI) was the largest contributor to Chinese female BC deaths and DALYs, while alcohol use was the greatest risk factor for Japanese and South Korean as well as Chinese males. The incident cases and deaths were expected to continue increase during 2020-2034 (except for Japanese female incident cases).

CONCLUSIONS

China had the greatest burden of BC among the three countries. Incident cases and deaths of BC were projected to increase over the next 15 years in China, particularly among Chinese males. Effective prevention and management strategies are urgently necessary for BC control in China.

Neuroendocrine pathways and breast cancer progression: a pooled analysis of somatic mutations and gene expression from two large breast cancer cohorts

Background

Experimental studies indicate that neuroendocrine pathways might play a role in progression of breast cancer. We aim to test the hypothesis that somatic mutations in the genes of neuroendocrine pathways influence breast cancer prognosis, through dysregulated gene expression in tumor tissue.

Methods

We conducted an extreme case–control study including 208 breast cancer patients with poor invasive disease-free survival (iDFS) and 208 patients with favorable iDFS who were individually matched on molecular subtype from the Breast Cancer Cohort at West China Hospital (WCH; N = 192) and The Cancer Genome Atlas (TCGA; N = 224). Whole exome sequencing and RNA sequencing of tumor and paired normal breast tissues were performed. Adrenergic, glucocorticoid, dopaminergic, serotonergic, and cholinergic pathways were assessed for differences in mutation burden and gene expression in relation to breast cancer iDFS using the logistic regression and global test, respectively.

Results

In the pooled analysis, presence of any somatic mutation (odds ratio = 1.66, 95% CI: 1.07–2.58) of the glucocorticoid pathway was associated with poor iDFS and a two-fold increase of tumor mutation burden was associated with 17% elevated odds (95% CI: 2–35%), after adjustment for cohort membership, age, menopausal status, molecular subtype, and tumor stage. Differential expression of genes in the glucocorticoid pathway in tumor tissue (P = 0.028), but not normal tissue (P = 0.701), was associated with poor iDFS. Somatic mutation of the adrenergic and cholinergic pathways was significantly associated with iDFS in WCH, but not in TCGA.

Conclusion

Glucocorticoid pathway may play a role in breast cancer prognosis through differential mutations and expression. Further characterization of its functional role may open new avenues for the development of novel therapeutic targets for breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09779-8.

Clinical characteristics and survival outcome of patients with estrogen receptor low positive breast cancer

Background

The benefit of endocrine therapy for patients with estrogen receptor (ER)-low (1%–10%) positive breast cancer is a matter for debate. We aimed to compare the clinical characteristics and survival outcome of ER-low patients with ER-high (＞10%) positive patients and ER-negative patients.

Methods

From the breast cancer database of our institution, we identified 5466 patients with known ER status who were diagnosed with early-stage breast cancer between January 2008 and December 2016. Variables associated with initiation of endocrine therapy were identified using multivariate logistic regression model. According to ER status, all patients were classified into ER-low (1%–10%), ER-high (>10%) and ER-negative subgroups. Fine and Gray competing risks regression was performed to compare the survival outcome of three subgroups.

Results

Age at diagnosis, ER status and progesterone receptor (PR) status were identified as correlates of initiation of endocrine therapy. ER-low patients were more likely to have advanced, PR-negative, human epidermal growth factor receptor 2 (HER2)-positive or grade Ⅲ disease compared to ER-high patients. Similar to ER-negative patients, ER-low patients presented increased rate of locoregional recurrence (LRR), distant recurrence (DR) and breast cancer mortality (BCM) than ER-high patients. Endocrine therapy showed nonsignificant trends toward lower LRR, DR and BCM in ER-low patients.

Conclusion

Similar to ER-negative patients, ER-low patients had more aggressive clinical characteristics and worse survival outcome than ER-high patients. ER-low patients appeared to benefit less from endocrine therapy. Randomized studies are needed to further explore the endocrine responsiveness of ER-low patients.

•

Age at diagnosis, ER status and PR status were associated with initiation of endocrine therapy.

•

ER-low patients had more aggressive clinical characteristics and worse survival outcome than ER-high patients.

•

ER-low patients appeared to benefit less from endocrine therapy than ER-high patients.

Association between age at initial diagnosis and post-metastasis mortality among women with recurrent metastatic breast cancer in China

Background

Little is known about whether age at initial diagnosis influences the prognosis of recurrent metastatic breast cancer (rMBC). Here, we analyzed the association between age at initial diagnosis and rMBC mortality in China.

Methods

A total of 1636 women diagnosed with rMBC between 1989 and 2020 at West China Hospital, Sichuan University were included in this study. The age at initial diagnosis was categorized as young (≤ 40 years), middle-aged (41–64 years) and elderly (≥ 65 years). Post-metastasis mortality was the primary outcome and its associated factors were analyzed by Cox proportional hazards models.

Results

During a median follow-up of 5.2 years after initial diagnosis of breast cancer, 620 deaths were identified. Compared with middle-aged patients, elderly patients had a 70% increased risk of post-metastasis mortality (95%CI, 1.24–2.33) after adjusting for demographics, tumor characteristics and treatment modes. Similarly, elderly patients were associated with a 75% increased risk of post-metastasis mortality (95%CI, 1.19–2.59) compared with young patients. Subgroup analyses also showed similar trends.

Conclusion

Our findings suggest that in breast cancer, elderly patients at initial diagnosis face a higher risk of post-metastasis mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09454-y.

Development and validation of prognostic nomograms for patients with metastatic small bowel adenocarcinoma: a retrospective cohort study

We aimed to explore factors associated with prognosis in patients with metastatic small bowel adenocarcinoma (SBA) as well as to develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS). Relevant information of patients diagnosed between 2004 and 2016 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms for predicting 1- and 3-year OS and CSS were established with potential risk factors screened from multivariate cox regression analysis. The discrimination and accuracy of the nomograms were assessed by concordance index (C-index), calibration plots, and the area under receiver operating characteristic curve (AUC). In total, 373 SBA patients with M1 category were enrolled. Multivariate analysis revealed that age, size and grade of primary tumor, primary tumor surgery, and chemotherapy were significant variables associated with OS and CSS. The C-index values of the nomogram for OS were 0.715 and 0.687 in the training and validation cohorts, respectively. For CSS, it was 0.711 and 0.690, respectively. Through AUC, decision curve analysis (DCA) and calibration plots, the nomograms displayed satisfactory prognostic predicted ability and clinical application both in the OS and CSS. Our models could be served as a reliable tool for prognostic evaluation of patients with metastatic SBA, which are favorable in facilitating individualized survival predictions and clinical decision-making.

Financial Toxicity and psychological distress in Adults with Cancer: A Treatment-based Analysis

Objective

To evaluate disparities in financial toxicity and psychological distress in patients with cancer as a function of treatment and reveal the relationship between financial toxicity and psychological distress.

Methods

This was a multicenter cross-sectional study. Patients were recruited from March 2017 to October 2018, and questionnaires were completed regarding their demographics, financial toxicity, and psychological distress. A multiple linear regression model was used to examine factors associated with financial and psychological distress.

Results

Significant financial toxicity and psychological distress occurred in 47.9% and 56.5% of patients, respectively. Financial toxicity (P ​= ​0.032) and psychological distress (P ​< ​0.001) were statistically different among the single chemotherapy, adjuvant therapy, and surgery groups. Multivariable analysis revealed that patients aged 50–59 years (P ​= ​0.035), 60–69 years (P ​= ​0.007), and 70 years or older (P ​= ​0.002) had higher the Comprehensive Score for financial Toxicity (COST) scores compared with patients less than 50 years old. Patients with personal annual income > 40,000 CNY reported higher COST scores than those who had < 20,000 CNY (P ​< ​0.001). Patients who had Urban Resident Basic Medical Insurance (URBMI) (P ​= ​0.030) or New Rural Cooperative Medical Scheme (NRCMS) (P ​= ​0.006) compared with Urban Employee Basic Medical Insurance (UEBMI) presented lower COST scores than patients with UEBMI. The multiple analysis model of psychological distress showed that an age of more than 70 years (P ​= ​0.010) was significantly associated with low the Distress Thermometer (DT) scores, and patients with colorectal cancer (P ​= ​0.009), the surgery group (P ​< ​0.001) and adjuvant therapy group (P ​< ​0.001) were significantly associated with high DT scores. The correlations between financial toxicity and psychological distress were mild but statistically significant in the chemotherapy-related treatment groups.

Conclusions

The research highlights the high rates of financial and psychological distress in adult patients. Multidimensional distress screening and psychosocial interventions should be provided for patients with cancer according to related factors.

Clinical Potential of lncRNA PPP1R26-AS1 in Breast Cancer and Its Contribution to Cancer Progression

Breast cancer has become the most leading diagnosed tumor worldwide in 2020. In this study, the biomarker potential and influence on the cellular function of lncRNA PPP1R26-AS1 was investigated in breast cancer. Expression levels of lncRNA PPP1R26-AS1 in breast tissues and cells were detected by RT-qPCR. Association between lncRNA PPP1R26-AS1 level and clinical parameters was investigated by Chi-square analysis. The prognostic potential was assessed by Kaplan-Meier and multivariate Cox regression analysis. Knockdown of lncRNA PPP1R26-AS1 was subjected to study the effect on cell proliferation, invasion, and migration by CCK-8 and transwell assay. The bind between PPP1R26-AS1 and miR-1226-3p was investigated. LncRNA PPP1R26-AS1 was highly expressed in breast tissues and cell lines. This upregulation was correlated with pTNM, positive ER status, luminal B subtype, positive nodal status, and shorter overall survival in breast cancer patients. Significant decreases in proliferation, migration, and invasion activity were observed upon knockdown of lncRNA PPP1R26-AS1. lncRNA PPP1R26-AS1 could act as ceRNA to bind with miR-1226-3p in breast cancer. LncRNA PPP1R26-AS1, as oncogenic lncRNA, could provide a new perspective on the development of prognostic biomarkers and a new approach in tailoring the treatment personalized in breast cancer.

Prognosis and Treatment of Metastatic Breast Cancer From A Real-World Scenario in China: A Retrospective Cohort Study

OBJECTIVES

Although metastatic breast cancer (MBC) is considered incurable, a specific subset of patients exhibits prolonged survival and even achieve a "cure". We retrospectively identified predictive prognostic factors and systemic therapy models to find this group of potentially cured patients.

METHODS

Consecutive patients diagnosed with MBC from 1991-2016 in West China Hospital were included. Univariate and multivariate analyses were conducted to assess the association of clinical factors and systemic therapy models with overall survival (OS), breast cancer-specific survival (BCSS) and progression-free survival (PFS).

RESULTS

The median OS was 63.4 months. Age, tumor size, lymph node metastasis, histologic grade, molecular subtype, site and number of metastases and metastasis-free interval (MFI) were related to the prognosis of MBC (P < .05). Patients with T1, N0-1, luminal A, bone metastasis, OMBC (oligometastatic breast cancer) or metastasis-free interval (MFI) ≥ 3 years showed the median OS more than 10 years (P < .001). Independent prognostic factors that correlated with OS and BCSS were residence, lymph node metastasis, histologic grade, molecular subtype, and site of metastasis (P < .05). The group of sequential chemo-endocrine therapy (ST) in hormone receptor (HR)-positive MBC patients showed the highest overall response rate (ORR) (P < .05). However, patients who received endocrine therapy (ET) showed the best OS, BCSS and PFS in the first two-line treatment, followed by ST and chemotherapy (CT) (P < .05).

CONCLUSIONS

Our study shows the predictive prognostic factors and systemic therapy models to facilitate patients likely to achieve long-term survival.

Disparities in Hepatocellular Carcinoma Survival by Insurance Status: A Population-Based Study in China

Objective: Health disparities related to basic medical insurance in China have not been sufficiently examined, particularly among patients with hepatocellular carcinoma (HCC). This study aims to investigate the disparities in HCC survival by insurance status in Tianjin, China.

Methods: This retrospective analysis used data from the Tianjin Basic Medical Insurance claims database, which consists of enrollees covered by Urban Employee Basic Medical Insurance (UEBMI) and Urban and Rural Resident Basic Medical Insurance (URRBMI). Adult patients newly diagnosed with HCC between 2011 and 2016 were identified and followed until death from any cause, withdrawal from UEBMI or URRBMI, or the latest data in the dataset (censoring as of December 31st 2017), whichever occurred first. Patients' overall survival during the follow-up was assessed using Kaplan-Meier and extrapolated by six parametric models. The hazard ratio (HR) and 95% confidence intervals (CI) were calculated with the adjusted Cox proportional hazards model including age at diagnosis, sex, baseline comorbidities and complications, baseline healthcare resources utilization and medical costs, tumor metastasis at diagnosis, the initial treatment after diagnosis and antiviral therapy during the follow-up.

Results: Two thousand sixty eight patients covered by UEBMI (N = 1,468) and URRBMI (N = 570) were included (mean age: 60.6 vs. 60.9, p = 0.667; female: 31.8 vs. 27.7%, p = 0.074). The median survival time for patients within the UEBMI and URRBMI were 37.8 and 12.2 months, and the 1-, 3-, 5-, 10-year overall survival rates were 63.8, 50.2, 51.0, 33.4, and 44.4, 22.8, 31.5, 13.1%, respectively. Compared with UEBMI, patients covered by URRBMI had 72% (HR: 1.72; 95% CI: 1.47–2.00) higher risk of death after adjustments for measured confounders above. The survival difference was still statistically significant (HR: 1.49; 95% CI: 1.21–1.83) in sensitivity analysis based on propensity score matching.

Conclusions: This study reveals that HCC patients covered by URRBMI may have worse survival than patients covered by UEBMI. Further efforts are warranted to understand healthcare disparities for patients covered by different basic medical insurance in China.

Treatment patterns and outcomes in older women with early breast cancer: a population-based cohort study in China

Background

Despite the proportion of elderly breast cancer patients has been consistently increasing, the optimal treatment modalities for this population have not been well explored. We summarized the treatment outcomes of these patients in our hospital.

Methods

Older patients with early breast cancer were identified from the Breast Cancer Information Management System at West China Hospital, Sichuan University (2000–2019). We compared tumor characteristics and treatment outcomes between the older group (65–74 years old) and the elderly group (≥75 years old). The Kaplan-Meier and Cox regression analysis were conducted to determine significant prognostic factors.

Results

In total, 1094 patients were included. The median follow-up time for this cohort was 59 months. The majority of patients underwent surgery and benefited from surgical treatment. Elderly group patients were less likely to receive adjuvant chemotherapy or postmastectomy radiotherapy (PMRT) compared to the older group. However, adjuvant chemotherapy was associated with improved overall survival (OS) (hazard ratio [HR] 0.521, 95% confidence interval [CI] 0.284–0.955, P = 0.035). Subgroup analysis revealed that patients with grade III disease best benefited from adjuvant chemotherapy. PMRT offered a significant improvement in local disease control, but not in OS. Furthermore, endocrine therapy improved the OS of HR-positive patients (HR 0.440, 95%CI 0.261–0.741, P = 0.002), especially for cases aged 65–74 years. Also, receipt of trastuzumab in HER2-positive patients was associated with better OS (HR 0.168, 95%CI 0.029–0.958, P = 0.045).

Conclusions

Our findings suggest that surgery, adjuvant chemotherapy, endocrine and targeted therapy are associated with improved OS in older breast cancer patients. Moreover, clinicopathological characteristics should be comprehensively considered when making treatment decisions for these patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07947-w.

Detection of breast cancer of various clinical stages based on serum FT-IR spectroscopy combined with multiple algorithms

BACKGROUND

Breast cancer screening is time consuming, requires expensive equipment, and has demanding requirements for doctors. Hence, a large number of breast cancer patients may miss screening and early treatment, which greatly threatens their health around the world. Infrared spectroscopy may be able to be used as a screening tool for breast cancer detection. Fourier transform infrared (FT-IR) spectroscopy of serum was combined with traditional machine learning algorithms to achieve an auxiliary diagnosis that could quickly and accurately distinguish patients with different stages of breast cancer, including stage 1 disease, from control subjects without breast cancer.

MATERIALS AND METHODS

FT-IR spectroscopy were performed on the serum of 114 non-cancer control subjects, 35 patients with stage I, 43 patients with stage II, and 29 patients with stage III & IV breast cancer. Due to the experimental sample imbalance, we used the oversampling to process the four classes of sample. The oversampling selected Synthetic Minority Oversampling Technique (SMOTE). Subsequently, we used the random discarding method in undersampling to do experiments as well. The average FT-IR spectroscopy results for the four groups showed differences in phospholipids, nucleic acids, lipids, and proteins between non-cancer control subjects and breast cancer patients at different stages. Based on these differences, four classification models were used to classify stage I, II, III & IV breast cancer patients and non-cancer control subjects. First, standard normal variate transformation (SNV) was used to preprocess the original data, and then partial least squares (PLS) was used for feature extraction. Finally, the five models were established including extreme learning machine (ELM), k-nearest neighbor (KNN), genetic algorithms based on support vector machine (GA-SVM), particle swarm optimization-support vector machine (PSO-SVM) and grid search-support vector machine (GS-SVM).

CONCLUSION

In oversampling experiment, the GS-SVM classifier obtained the highest average classification accuracy of 95.45 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 90 %; breast cancer stage II was 84.62 %; and breast cancer stage III & IV was 100 %. In undersampling experiment, the GA-SVM model obtained the highest average classification accuracy of 100 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 100 %; breast cancer stage II was 100 %; and breast cancer stage III & IV was 100 %. The results show that FT-IR spectroscopy combined with powerful classification algorithms has great potential in distinguishing patients with different stages of breast cancer from non-cancer control subjects. In addition, this research provides a reference for future multiclassification studies of cervical cancer, ovarian cancer and other female high-incidence cancers through serum FT-IR spectroscopy.