Background: Since Mohamed et al. analyzed 2326 orthopedic cases in 2002 and believed that the POSSUM formula can be directly used to predict postoperative morbidity and mortality in orthopedic patients, applications of POSSUM and P-POSSUM scores in the hip fracture surgery have been mostly reported in the field of orthopedics, but there are still some inconsistencies in the related reports. Methods: The electronic library was searched for all literature that met the purpose from its inception to 2021. Relative risk (RR) was selected to evaluate whether the model could be used to assess the risk of surgery in patients with elderly hip fractures. Finally, sensitivity analyses and subgroup analyses were performed. Results: Thirteen studies were finally included, including 9 retrospective and 4 prospective studies.The morbidity analysis includes 11 studies, and the result was RR = 1.07 (95% CI 0.93–1.24), The mortality analysis includes 11 studies on POSSUM and 5 studies on P-POSSUM. The results of mortality by POSSUM and by P-POSSUM were RR = 1.93 (95% CI 1.21–3.08) and RR = 1.15 (95% CI 0.89–1.50), respectively. POSSUM had more accuracy to predict mortality for sample < 200 subgroup(RR = 2.45; 95% CI 0.71–8.42) than sample > 200 subgroup(RR = 1.59; 95% CI 1.06–2.40), and in the subgroup of hip fractures that did not distinguish between specific fracture types(RR = 1.69, 95% CI 0.87–3.32) than intertrochanteric neck fracture subgroup(RR = 5.04, 95% CI 1.07–23.75) and femoral femoral fracture subgroup(RR = 1.43,95% CI 1.10–1.84). Conclusion: POSSUM can be used to predict morbidity in elderly hip fractures. The P-POSSUM was more accurate in predicting mortality in elderly hip fracture patients compared to the POSSUM, whose predictive value for mortality was influenced by the sample size and type of fracture studied. In addition, we believe that appropriate improvements to the POSSUM system are needed to address the characteristics of orthopedic surgery.

Background: Osteosarcoma (OS) is the most common primary tumor of bone in adolescents, and its survival rate is generally less than 20% when metastases occur. Necroptosis, a novel form of programmed necrotic cell death distinct from apoptosis, has been increasingly recognized as a promising therapeutic strategy. This study sought to identify long non-coding RNAs (lncRNAs) associated with necrotizing apoptosis to predict prognosis and target drug use to improve patient survival.Methods: Transcriptomic data and clinical data from 85 OS patients with survival time data and expression profiles from 85 random normal adipose tissue samples were extracted from the UCSC Xena website (http://xena.ucsc.edu/). Nine necroptosis-associated differential prognostic lncRNAs were then identified by analysis of variance, correlation analysis, univariate Cox (uni-Cox) regression, and Kaplan–Meier analysis. Then, patients were randomized into training or testing groups. According to uni-Cox, we obtained prognostic lncRNAs in the training group and intersected them with the abovementioned nine lncRNAs to obtain the final necrotizing apoptosis–related differential prognostic lncRNAs (NRlncRNAs). Next, we performed the least absolute shrinkage and selection operator (LASSO) to construct a risk model of NRlncRNAs. Kaplan–Meier analysis, ROC curves, nomograms, calibration curves, and PCA were used to validate and evaluate the models and grouping. We also analyzed the differences in tumor immunity and drugs between risk groups.Results: We constructed a model containing three NRlncRNAs (AL391121.1, AL354919.2, and AP000851.2) and validated its prognostic predictive power. The value of the AUC curve of 1-, 3-, and 5-year survival probability was 0.806, 0.728, and 0.731, respectively. Moreover, we found that the overall survival time of patients in the high-risk group was shorter than that in the low-risk group. GSEA and ssGSEA showed that immune-related pathways were mainly abundant in the low-risk group. We also validated the differential prediction of immune checkpoint expression, tumor immunity, and therapeutic compounds in the two risk groups.Conclusion: Overall, NRlncRNAs have important functions in OS, and these three NRlncRNAs can predict the prognosis of OS and provide guidance for immunotherapy in OS.

N1-methyladenosine methylation (m¹A), as an important RNA methylation modification, regulates the development of many tumours. Metabolic reprogramming is one of the important features of tumour cells, and it plays a crucial role in tumour development and metastasis. The role of RNA methylation and metabolic reprogramming in osteosarcoma has been widely reported. However, the potential roles and mechanisms of m¹A-related metabolic genes (MRmetabolism) in osteosarcoma have not been currently described. All of MRmetabolism were screened, then selected two MRmetabolism by least absolute shrinkage and selection operator and multifactorial regression analysis to construct a prognostic signature. Patients were divided into high-risk and low-risk groups based on the median riskscore of all patients. After randomizing patients into train and test cohorts, the reliability of the prognostic signature was validated in the whole, train and test cohort, respectively. Subsequently, based on the expression profiles of the two MRmetabolism, we performed consensus clustering to classify patients into two clusters. In addition, we explored the immune infiltration status of different risk groups and different clusters by CIBERSORT and single sample gene set enrichment analysis. Also, to better guide individualized treatment, we analyzed the immune checkpoint expression differences and drug sensitivity in the different risk groups and clusters. In conclusion, we constructed a MRmetabolism prognostic signature, which may help to assess patient prognosis, immunotherapy response.

Background: Since Mohamed et al analyzed 2326 orthopedic cases in 2002 and believed that the POSSUM formula can be directly used to predict postoperative morbidity and mortality in orthopedic patients, applications of POSSUM and P-POSSUM scores in the hip fracture surgery have been mostly reported in the field of orthopedics, but there are still some inconsistencies in the related reports. Methods: The electronic library was searched for all literature that met the purpose from its inception to 2021. Relative risk (RR) was selected to evaluate whether the model could be used to assess the risk of surgery in patients with elderly hip fractures. Finally, sensitivity analyses and subgroup analyses were performed.Results: Thirteen studies were finally included, including 9 retrospective and 4 prospective studies.The morbidity analysis includes 11 studies, and the result was RR=1.07 (95%CI: 0.93-1.24), The mortality analysis includes 11 studies on POSSUM and 5 studies on P-POSSUM. The results of mortality by POSSUM and by P-POSSUM were RR=1.93 (95%CI: 1.21-3.08) and RR=1.15 (95%CI: 0.89-1.50), respectively. POSSUM had more accuracy to predict mortality for sample200 subgroup (RR=1.59; 95%CI: 1.06-2.40), and in the subgroup of hip fractures that did not distinguish between specific fracture types(RR=1.69, 95%CI: 0.87-3.32) than intertrochanteric neck fracture subgroup(RR=5.04,95%CI: 1.07-23.75) and femoral femoral fracture subgroup(RR=1.43 ,95% CI: 1.10-1.84).Conclusion: POSSUM can be used to predict morbidity in elderly hip fractures. The P-POSSUM was more accurate in predicting mortality in elderly hip fracture patients compared to the POSSUM, whose predictive value for mortality was influenced by the sample size and type of fracture studied. In addition, we believe that appropriate improvements to the POSSUM system are needed to address the characteristics of orthopaedic surgery.

Human sperm-associated antigen 4 (SPAG4), as a member of the cancer-testis antigen(CTA) family, is considered to be a potential cancer marker. However, It is not known whether SPAG4 functions in the tumor immune microenvironment through some common mechanism. Here, we explored the oncogenic role of SPAG4 in 33 human tumors based on TCGA and GEO databases using web-based tools such as TIMER2.0, GEPIA2, TISIDE, ROC plotter, TIDE, and Western Blot experiments. The results showed that SPAG4 was highly expressed in 21 tumors and predicted a poor clinical prognosis in most tumors. Moreover, SPAG4 has an important role in the tumor microenvironment and is likely to be involved in the regulation of the immune microenvironment. Most importantly, SPAG4 expression was significantly associated with drug resistance and immune checkpoint blockade therapy in tumor patients, and could potentially regulate the occurrence of immune escape. In conclusion, our study suggests that SPAG4 is an immune oncogenic molecule that can be used as a biomarker for cancer detection, prognosis, treatment design and follow-up.