Journal of the National Cancer Center最新文献

Objective

This is a comprehensive overview of long-term cancer survival in Zhejiang Province, China. Hybrid analysis, a combination of cohort and period analysis, has been proposed to derive up-to-date cancer survival estimates. Using this approach, we aimed to timely and accurately analyze the 5-year relative survival (RS) and net survival (NS) in cancer registries of Zhejiang Province, China.

Methods

A total of 255,725 new cancer cases diagnosed during 2013–2017 were included in 14 cancer registries in Zhejiang Province, China, with a follow-up on vital status until the end of 2019. The hybrid analysis was used to calculate the 5-year RS and 5-year NS during 2018–2019 for overall and stratifications by sex, cancer type, region, and age at diagnosis.

Results

During 2018–2019, the age-standardized 5-year RS and NS for overall cancer in Zhejiang was 47.5% and 48.6%, respectively. The age-standardized 5-year RS for cancers of women (55.4%) was higher than that of men (40.0%), and the rate of urban areas (49.7%) was higher than that of rural areas (43.1%). The 5-year RS declined along with age, from 84.4% for ages <45 years to 23.7% for ages >74 years. Our results of the RS and NS showed the similar trend and no significant difference. The top five cancers with top age-standardized 5-year RS were thyroid cancer (96.0%), breast cancer (84.3%), testicular cancer (79.9%), prostate cancer (77.2%), and bladder cancer (70.6%), and the five cancers with the lowest age-standardized 5-year RS were pancreatic cancer (6.0%), liver cancer (15.6%), gallbladder cancer (17.1%), esophageal cancer (22.7%), and leukemia (31.0%).

Conclusions

We reported the most up-to-date 5-year cancer RS and NS in Zhejiang Province, China for the first time, and found that the 5-year survival for cancer patients in Zhejiang during 2018–2019 was relatively high. The population-based cancer registries are recognized as key policy tools that can be used to evaluate both the impact of cancer prevention strategies and the effectiveness of health systems.

Heart rate variability (HRV) analysis provides an assessment of cardiac vagal tone and consequently global cardiac health as well as systemic condition. In systemic diseases such as cancer and during treatments that affect the whole body, like chemotherapy, the vagus nerve activity is low and deregulated. Some studies focus on using HRV to predict mortality in oncology. However, in cancer patients, systemic alterations substantially increase artifacts during HRV measurement, especially atrial ectopic beats. Moreover, HRV may be altered by various factors (duration and time of measurement, breathing, drugs, and other confounding factors) that alter each metric in different ways. The Standard Deviation of all Normal to Normal intervals (SDNN) is the most commonly used metric to evaluate HRV in oncology, but it does not appear to be specific to the cardiac vagal tone. Thus, cardiac vagal activity diagnosis and vital prognosis of cancer patients can be biased. Our review presents the main HRV metrics that can be currently used in oncology studies and their links with vagus nerve and cancer. We present the influence of external factors and the required duration and time of measurement. Considering all these parameters, this review proposes seven key points for an assessment of HRV and cardiac vagal tone in patients with cancer.

Renal cancer is one of the most common malignancies of the urinary system, and the number of deaths continues to increase. The standardized management of the diagnosis and treatment of renal cancer is challenging due to the great differences in the diagnosis and treatment of renal cancer in different regions. The Renal Cancer Expert Committee of the National Cancer Quality Control Center (NCQCC) identified a lack of authoritative quality control standards as an opportunity to utilize its multidisciplinary membership to improve the standardized diagnosis and treatment of renal cancer. The Renal Cancer Expert Committee of the NCQCC aims to promote quality control and national standardization, uniformity, and normalization of renal cancer diagnosis and treatment, which ultimately improved the survival rate and quality of life of renal cancer patients. A panel of experts with renal cancer surgery, renal cancer medicine, medical imaging, pathology and radiotherapy were drawn together and determined the quality control standards for the standardized diagnosis and treatment of renal cancer. The Indices includes 20 items that cover all key areas in the diagnosis and treatment of renal cancer, such as standard diagnosis, surgery treatment, systemic treatment, and prognostic evaluation.

Background

The National Cancer Center (NCC) of China regularly reports the nationwide statistics on cancer incidence and mortality in China. The International Agency for Research on Cancer (IARC) calculates and publishes the cancer burden of countries around the world every two years. To ensure consistency between the actual surveillance data in China and the data published by IARC, NCC has received approval from the National Health Commission and IARC to simultaneously release the cancer burden data for China in GLOBOCAN 2022.

Methods

There were a total of 700 registries reporting high-quality data on cancer incidence and mortality across China in 2018, of which 106 registries with continuous monitoring from 2010 to 2018 were used to establish an age-period-cohort model to simulate the trend of cancer incidence and mortality and to estimate the incidence and mortality in China in 2022. In addition, we analyzed the temporal trends of age-standardized cancer incidence and mortality from 2000 to 2018 using data from 22 continuous cancer registries.

Results

It was estimated about 4,824,700 new cancer cases and 2,574,200 new cancer deaths occurred in China in 2022. Cancers of the lung, colon-rectum, thyroid, liver and stomach were the top five cancer types, accounting for 57.42% of new cancer cases. Cancers of the lung, liver, stomach, colon-rectum and esophagus were the five leading causes of cancer deaths, accounting for 67.50% of total cancer deaths. The crude rate and age-standardized incidence rate (ASIR) were 341.75 per 100,000 and 201.61 per 100,000, respectively. The crude mortality rate was 182.34 per 100,000 and the age-standardized mortality rate (ASMR) was 96.47 per 100,000. The ASIR of all cancers combined increased by approximately 1.4% per year during 2000–2018, while the ASMR decreased by approximately 1.3% per year. We observed decreasing trends in ASIR and ASMR for cancers of the esophagus, stomach, and liver, whereas the ASIR increased significantly for cancers of the thyroid, prostate, and cervix.

Conclusions

Cancer remains a major public health concern in China, with a cancer profile that reflects the coexistence of developed and developing regions. Sustained implementation of prevention and control measures has resulted in significant reductions in the incidence and mortality rates of certain historically high incidence cancers, such as esophageal, stomach and liver cancers. Adherence to the guidelines of the Healthy China Action Plan and the Cancer Prevention and Control Action Plan, along with continued efforts in comprehensive risk factor control, cancer screening, early diagnosis and treatment, and standardization of diagnostic and therapeutic protocols, are key strategies to effectively mitigate the increasing cancer burden by 2030.

Objective

Circulating tumor DNA (ctDNA) is increasingly being used as a potential prognosis biomarker in patients of breast cancer. This review aims to assess the clinical value of ctDNA in outcome prediction in breast cancer patients throughout the whole treatment cycle.

Methods

PubMed, Web of Science, Embase, Cochrane Library, Scopus, and clinical trials.gov were searched from January 2016 to May 2022. Conference abstracts published in last three years were also included. The following search terms were used: ctDNA OR circulating tumor DNA AND breast cancer OR breast carcinoma. Only studies written in English languages were included. The following pre-specified criteria should be met for inclusion: (1) observational studies (prospective or retrospective), randomized control trials, case-control studies and case series studies; (2) patients with breast cancer; (3) ctDNA measurement; (4) clinical outcome data such as objective response rate (ORR), pathological complete response (pCR), relapse-free survival (RFS), overall survival (OS), and so on. The random-effect model was preferred considering the potential heterogeneity across studies. The primary outcomes included postoperative short-term outcomes (ORR and pCR) and postoperative long-term outcomes (RFS, OS, and relapse). Secondary outcomes focused on ctDNA detection rate.

Results

A total of 30 studies, comprising of 19 cohort studies, 2 case-control studies and 9 case series studies were included. The baseline ctDNA was significantly negatively associated with ORR outcome (Relative Risk [RR] = 0.65, 95% confidence interval [CI]: 0.50–0.83), with lower ORR in the ctDNA-positive group than ctDNA-negative group. ctDNA during neoadjuvant therapy (NAT) treatment was significantly associated with pCR outcomes (Odds Ratio [OR] = 0.15, 95% CI: 0.04–0.54). The strong association between ctDNA and RFS or relapse outcome was significant across the whole treatment period, especially after the surgery (RFS: Hazard Ratio [HR] = 6.74, 95% CI: 3.73–12.17; relapse outcome: RR = 7.11, 95% CI: 3.05–16.53), although there was heterogeneity in these results. Pre-operative and post-operative ctDNA measurements were significantly associated with OS outcomes (pre-operative: HR = 2.03, 95% CI: 1.12–3.70; post-operative: HR = 6.03, 95% CI: 1.31–27.78).

Conclusions

In this review, ctDNA measurements at different timepoints are correlated with evaluation indexes at different periods after treatment. The ctDNA can be used as an early potential postoperative prognosis biomarker in breast cancer, and also as a reference index to evaluate the therapeutic effect at different stages.

Objective

To develop a deep learning model to predict lymph node (LN) status in clinical stage IA lung adenocarcinoma patients.

Methods

This diagnostic study included 1,009 patients with pathologically confirmed clinical stage T1N0M0 lung adenocarcinoma from two independent datasets (699 from Cancer Hospital of Chinese Academy of Medical Sciences and 310 from PLA General Hospital) between January 2005 and December 2019. The Cancer Hospital dataset was randomly split into a training cohort (559 patients) and a validation cohort (140 patients) to train and tune a deep learning model based on a deep residual network (ResNet). The PLA Hospital dataset was used as a testing cohort to evaluate the generalization ability of the model. Thoracic radiologists manually segmented tumors and interpreted high-resolution computed tomography (HRCT) features for the model. The predictive performance was assessed by area under the curves (AUCs), accuracy, precision, recall, and F1 score. Subgroup analysis was performed to evaluate the potential bias of the study population.

Results

A total of 1,009 patients were included in this study; 409 (40.5%) were male and 600 (59.5%) were female. The median age was 57.0 years (inter-quartile range, IQR: 50.0–64.0). The deep learning model achieved AUCs of 0.906 (95% CI: 0.873–0.938) and 0.893 (95% CI: 0.857–0.930) for predicting pN0 disease in the testing cohort and a non-pure ground glass nodule (non-pGGN) testing cohort, respectively. No significant difference was detected between the testing cohort and the non-pGGN testing cohort (P = 0.622). The precisions of this model for predicting pN0 disease were 0.979 (95% CI: 0.963–0.995) and 0.983 (95% CI: 0.967–0.998) in the testing cohort and the non-pGGN testing cohort, respectively. The deep learning model achieved AUCs of 0.848 (95% CI: 0.798–0.898) and 0.831 (95% CI: 0.776–0.887) for predicting pN2 disease in the testing cohort and the non-pGGN testing cohort, respectively. No significant difference was detected between the testing cohort and the non-pGGN testing cohort (P = 0.657). The recalls of this model for predicting pN2 disease were 0.903 (95% CI: 0.870–0.936) and 0.931 (95% CI: 0.901–0.961) in the testing cohort and the non-pGGN testing cohort, respectively.

Conclusions

The superior performance of the deep learning model will help to target the extension of lymph node dissection and reduce the ineffective lymph node dissection in early-stage lung adenocarcinoma patients.

Chimeric antigen receptor (CAR) T-cell therapy has emerged as a groundbreaking approach in cancer treatment, utilizing the immune system's capabilities to combat malignancies. This innovative therapy involves extracting T-cells from a patient's blood, genetically modifying them to target specific cancer cells, and reinfusing them back into the patient's body. The genetically modified T-cells then seek out and eliminate cancer cells, offering a promising therapeutic strategy. Since its initial approval in 2017, CAR-T therapy has witnessed remarkable advancements and updates. Notably, CAR-T therapy, which was initially developed for hematological malignancies, has expanded its scope to target solid tumors. Currently, clinical trials are underway to explore the efficacy of CAR-T therapy in treating various solid tumors, such as lung cancer, breast cancer, and ovarian cancer. These trials hold great potential to revolutionize cancer treatment and provide new hope to patients with challenging-to-treat solid tumors. In this mini-review, we present an overview of CAR-T therapy's mechanisms, emphasizing its role in targeting cancer cells and the potential therapeutic benefits. Additionally, we discuss the recent progress and updates in CAR-T therapy, particularly its application in treating solid tumors, and highlight the ongoing clinical trials aimed at broadening its therapeutic horizon. The evolving landscape of CAR-T therapy signifies a promising direction in cancer therapeutics, with the potential to revolutionize the treatment of both hematological and solid tumor malignancies.

Lung cancer is the leading cause of cancer-related deaths worldwide. Bone is a common metastatic site of lung cancer, about 50% of bone metastatic patients will experience skeletal related events (SREs). SREs not only seriously impact the quality of life of patients, but also shorten their survival time. The treatment of bone metastasis requires multi-disciplinary therapy (MDT) and development of individualized treatment plan. In order to standardize the diagnosis and treatment of bone metastasis in lung cancer, the expert group of the MDT Committee of the Chinese Medical Doctor Association has developed the expert consensus on the diagnosis and treatment of lung cancer bone metastasis.