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This article combs and summarizes the entire process of rare disease selection and priority theme determination, including the application and preliminary review of rare diseases, standardization of disease theme information, the evaluation methods of evidence sorting and disease selection for priority selection of disease themes, and other aspects of the content were analyzed in depth. It is expected to provide reference for the subsequent selection of rare diseases, improve the fairness, rationality and scientificity of rare disease selection, and further promote research and decision-making in China′s rare disease-related fields.

The National Health Commission of the People′s Republic of China and six other departments jointly released the Second Catalog of Rare Diseases, which expanded the definition of rare diseases in China. The expansion of the catalog means greater attention to rare diseases at the national level, and is also expected to accelerate the launch of relevant rare disease drugs and benefit more rare disease patients. When the new rare disease catalog released, it is necessary to quickly sort out the availability of drugs and find out the base number for the advancement of subsequent relevant measures. This paper searched official medical information websites and medical databases such as the National Medical Products Administration (NMPA), the Center for Drug Evaluation (CDE), and foreign drug regulatory agencies, and sorted out and summarized the subject categories of diseases included in the Second Catalog of Rare Diseases, the corresponding global research and development and implementation of drugs, as well as the medical insurance access situation in China, elaborates on the differences in the accessibility of orphan drugs at home and abroad. As China′s prevention, treatment and protection of rare diseases has reached a new point, plans and prospects are made for the introduction of relevant policies in the future, as well as the promotion of research and development and protection and other key tasks.

Health security for rare diseases has aroused much attention in the society nowadays, In this article, we analyzed in-depth the construction of rare diseases health security in China by studying the literature reviews, expert interviews, and reports of pilot policy investigations. We conclude in the study that it is an important step to constructing a multiple health security system for the rare disease making the basic health security as the cornerstone. For rare medications and treatments that cannot be covered by the current national health insurance, it is necessary to build an specific funding for rare disease funding as a means of safeguard. Finally, for those who are financially disadvantages, the system should involve relief and philanthropy to help them. By constructing a multiple health security system, rare diseases patients in our country will get a well-covered health care.

Lanthanide‐based upconversion molecular complexes have potential application in diverse fields and attracted considerable research interest in recent years. However, the similar coordination reactivity of lanthanide ions has constrained the designability of target molecule with well‐defined structure, and many attempts obtained statistical mixtures. Herein, an ion‐paired Yb−Eu heteronuclear complex [Eu(TpPy)2][Yb(ND)4] (TpPy=tris[3‐(2‐pyridyl)pyrazolyl]hydroborate, ND=3‐cyano‐2‐methyl‐1,5‐naphthyridin‐4‐olate) was designed and synthesized. Thanks to the radius difference between Eu3+ (1.07 Å) and Yb3+ (0.98 Å) ions, the hexadentate TpPy ligand was selected to coordinate with Eu3+ and the Yb3+ with a smaller radius was chelated by bidentate ND ligand. As a result, the sites of Eu3+ and Yb3+ in the complex can be clarified by high‐resolution mass spectrometry and single‐crystal structure analysis. Upon the excitation of Yb3+ at 980 nm, the upconversion emission of Eu3+ was realized through a cooperative sensitization process. Furthermore, [Eu(TpPy)2][Yb(ND)4] demonstrated excellent photostability during continuous high‐power density 980 nm laser irradiation, with a LT95 (the time to 95 % of the initial emission intensity) of 420 minutes. This work provides the first example of a pure ion‐paired Yb−Eu heteronuclear complex upconversion system and may bring insights into rational design of lanthanide‐based upconversion molecular complexes. [ABSTRACT FROM AUTHOR]

Cancer is a heterogeneous disease, and rapid progress in sequencing and -omics technologies has enabled researchers to characterize tumors comprehensively. This has stimulated an intensive interest in studying how risk factors are associated with various tumor heterogeneous features. The Cancer Prevention Study-II (CPS-II) cohort is one of the largest prospective studies, particularly valuable for elucidating associations between cancer and risk factors. In this article, we investigate the association of smoking with novel colorectal tumor markers obtained from targeted sequencing. However, due to cost and logistic difficulties, only a limited number of tumors can be assayed, which limits our capability for studying these associations. Meanwhile, there are extensive studies for assessing the association of smoking with overall cancer risk and established colorectal tumor markers. Importantly, such summary information is readily available from the literature. By linking this summary information to parameters of interest with proper constraints, we develop a generalized integration approach for polytomous logistic regression model with outcome characterized by tumor features. The proposed approach gains the efficiency through maximizing the joint likelihood of individual-level tumor data and external summary information under the constraints that narrow the parameter searching space. We apply the proposed method to the CPS-II data and identify the association of smoking with colorectal cancer risk differing by the mutational status of APC and RNF43 genes, neither of which is identified by the conventional analysis of CPS-II individual data only. These results help better understand the role of smoking in the etiology of colorectal cancer. for this article are available online. [ABSTRACT FROM AUTHOR]

Accurate risk assessment is critical in clinical decision‐making. It entails the projected risk based on a risk prediction model agreeing with the observed risk in the target cohort. However, the model often over‐ or under‐estimates the risk. Building a new model for the target cohort would be ideal but costly. It is therefore of great interest to recalibrate an existing model for the target cohort. Existing methods have been proposed to recalibrate the model by leveraging the disease incidence rates from the target cohort. However, they assume the same covariate distribution across cohorts and when the assumption is violated, the recalibrated model can be substantially biased. Further, recalibration is also complicated by the two‐phase sampling design that is commonly used for developing risk prediction models. In this paper, we develop a weighted estimating‐equation approach accounting for the two‐phase design and combine it with a weighted empirical likelihood that leverages the summary information on both disease incidence rates and covariates from the target cohort. We provide a resampling‐based inference procedure. Our extensive simulation results show that using the summary information from the target population, the proposed recalibration method yields nearly unbiased risk estimates under a wide range of scenarios. An application to a colorectal cancer study also illustrates that the proposed method yields a well‐calibrated model in the target cohort. [ABSTRACT FROM AUTHOR]

Predicting risks of chronic diseases has become increasingly important in clinical practice. When a prediction model is developed in a cohort, there is a great interest to apply the model to other cohorts. Due to potential discrepancy in baseline disease incidences between different cohorts and shifts in patient composition, the risk predicted by the model built in the source cohort often under- or over-estimates the risk in a new cohort. In this article, we assume the relative risks of predictors are the same between the two cohorts, and propose a novel weighted estimating equation approach to recalibrating the projected risk for the targeted population through updating the baseline risk. The recalibration leverages the knowledge about survival probabilities for the disease of interest and competing events, and summary information of risk factors from the target population. We establish the consistency and asymptotic normality of the proposed estimators. Extensive simulation demonstrate that the proposed estimators are robust, even if the risk factor distributions differ between the source and target populations, and gain efficiency if they are the same, as long as the information from the target is precise. The method is illustrated with a recalibration of colorectal cancer prediction model. [ABSTRACT FROM AUTHOR]