Stereotactic body radiotherapy (SBRT) is a novel noninvasive treatment for hepatocellular carcinoma. SBRT can achieve effective local control, but it requires a relatively high input of resources; this systematic review was performed to assess the cost effectiveness of SBRT in the treatment of hepatocellular carcinoma to provide a basis for government pricing and medical insurance decision-making. The PubMed, EMBASE, Cochrane Library, CNKI, Wanfang and SinoMed databases were searched to collect economic evaluations of SBRT for the treatment of hepatocellular carcinoma from the date of database inception through December 31, 2018. Two reviewers independently screened the studies, extracted the data and performed a descriptive analysis of the basic characteristics, methods of economic evaluation and main results, as well as the quality and heterogeneity of the reports. A total of 5 studies were included. Among them, the level of heterogeneity was relatively acceptable, with a median score of 90%. Four studies were cost-utility analyses (CUAs), and 1 was a cost-effectiveness analysis (CEA). The incremental cost effectiveness ratio (ICER) for sorafenib compared to SBRT was US $114,795 per quality-adjusted life year gained (cost/QALY) in patients with advanced hepatocellular carcinoma. The ICER for proton beam therapy compared to SBRT was US $6465 in patients with inoperable advanced hepatocellular carcinoma. The ICER for SBRT compared to RFA was US $164,660 for patients with unresectable colorectal cancer (CRC) with liver metastases and US $56,301 for patients with early-stage hepatocellular carcinoma. For patients with inoperable localized hepatocellular carcinoma, compared with RFA–SBRT therapy, the ICERs for SBRT–SBRT and SBRT–RFA were US $558,679 and US $2197,000, respectively; RFA–RFA was dominated. In conclusion, there is limited evidence suggesting that SBRT could be cost-effective for highly specific subpopulations of HCC patients, and further economic evaluations based on randomized controlled trials (RCTs) or cohort studies are needed.

One important challenge for global development is aging. China is one of the world's countries with the highest elderly population and the most rapid aging; in 2022, the percentage of the population over 65 was 14.9%; by 2050, it is expected to rise to 26.1%. China's health security, elderly care, and healthcare services are facing serious challenges as a result of this aging trend. With 80% of provinces including medical and elderly care in national basic public health care programs, China has adopted a proactive national plan to combat population aging. Moreover, geriatric departments have been established at 69.3% of public general hospitals at secondary and higher tiers, 48% of provinces have devises preventive interventions for disability and dementia in the elderly, 48 percent of provinces are serving as test regions for medical care related to rehabilitation, and 49 cities are involved in long-term care insurance (LTCI) trials that encompass 170 million people. There are 4,259 medical and health care facilities that provide hospice care services, 152 hospice care pilot regions, and 87,000 pairs of contracts between medical and health care facilities and elderly care providers. These developments provide a strong basis, but there are still major obstacles to overcome. The Chinese Government is urged to adopt early preventive measures, offer more ongoing, practical, and cost-effective diagnostic and treatment services, allocate resources equitably, and use intelligent technologies to enhance elderly care. The ultimate goals are to lessen the financial burden, enhance the health of the elderly, and offer a vital global resource.

With the increasing application of artificial intelligence (AI) in medicine and healthcare, AI technologies have the potential to improve the diagnosis, treatment, and prognosis of rare diseases. Presently, existing research predominantly focuses on the areas of diagnosis and prognosis, with relatively fewer studies dedicated to the domain of treatment. The purpose of this review is to systematically analyze the existing literature on the application of AI in the treatment of rare diseases. We searched three databases for related studies, and established criteria for the selection of retrieved articles. From the 407 unique articles identified across the three databases, 13 articles from 8 countries were selected, which investigated 10 different rare diseases. The most frequently studied rare disease group was rare neurologic diseases (n = 5/13, 38.46%). Among the four identified therapeutic domains, 7 articles (53.85%) focused on drug research, with 5 specifically focused on drug discovery (drug repurposing, the discovery of drug targets and small-molecule inhibitors), 1 on pre-clinical studies (drug interactions), and 1 on clinical studies (information strength assessment of clinical parameters). Across the selected 13 articles, we identified total 32 different algorithms, with random forest (RF) being the most commonly used (n = 4/32, 12.50%). The predominant purpose of AI in the treatment of rare diseases in these articles was to enhance the performance of analytical tasks (53.33%). The most common data source was database data (35.29%), with 5 of these studies being in the field of drug research, utilizing classic databases such as RCSB, PDB and NCBI. Additionally, 47.37% of the articles highlighted the existing challenge of data scarcity or small sample sizes.

Background: The maintenance treatment of ESRD puts a great burden on individual patients, society, and the country of China as a whole. Hemoperfusion plus hemodialysis (HP + HD) in ESRD patients can yield modified outcomes such as prolonged life expectancy and improved dialysis quality and quality of life. This study aimed to systematically analyze the effect of HP + HD on the overall survival (OS) rates of ESRD patients and to provide support for clinical decision-making. Methods: A computerized search was performed in the PubMed, Embase, Cochrane Library, CNKI, WanFang Data and SinoMed databases for relevant original research articles. Studies were included or excluded based on their compliance with predefined selection criteria. Results: Twelve studies were included in the qualitative synthesis and quantitative synthesis (meta-analysis). The meta-analysis showed that the 1-year OS rate (odds ratio [OR]: 3.35, 95% CI: 1.89, 5.91, p < 0.05), 2-year OS rate (OR: 2.88, 95% CI: 1.84, 4.53, p < 0.05), and 5-year OS rate (χ2 = 4.3092, p < 0.05) of patients with ESRD treated with HP + HD were better than those treated with HD, but there was no significant difference in 3-year OS rate (OR: 1.97, 95% CI: 0.76, 5.06, p > 0.05). Subgroup analysis showed the same outcomes in different study designs (1-year OS rate: randomized controlled trials [RCTs]: OR: 4.38, 95% CI: 1.61, 11.88, p < 0.05; cohort studies: OR: 2.90, 95% CI: 1.44, 5.85, p < 0.05; 2-year OS rate: RCTs: OR: 2.99, 95% CI: 1.84, 4.84, p < 0.05) and different age-groups (1-year OS rate: 45–50 years: OR: 3.19, 95% CI: 1.55, 6.57, p < 0.05; 55–60 years: OR: 3.37, 95% CI: 1.07, 10.61, p < 0.05; 2-year OS rate: 50–55 years: OR: 2.86, 95% CI: 1.59, 5.16, p < 0.05: 60–65 years: OR: 4.41, 95% CI: 1.19, 16.30, p < 0.05). Conclusions: This meta-analysis suggests that the OS rates of ESRD patients treated with HP + HD were better than those of patients treated with HD. A speculative hypothesis for why this is the case may be that HP + HD can achieve the complementary elimination of metabolites, effectively preventing and treating complications caused by long-term dialysis and prolonging life expectancy. Therefore, HP + HD should be widely used in ESRD patients.