Type 2 sclerotic Modic change affect fusion result in patients undergoing PLIF with pedicle screw instrumentation: a retrospective study.

BACKGROUND: Bony fusion rate was significantly lower in patients with type 3 Modic change than patients with normal endplates. It is not known whether there are relevant differences in fusion efficiency among patients with type 2 sclerotic Modic change or non-sclerotic Modic change, or no Modic change. METHODS: A retrospective study contained 196 lumbar segments in 123 subjects undergoing posterior lumbar interbody fusion (PLIF) with pedicle screw instrumentation (PSI) to assess the effect of type 2 sclerotic Modic change on fusion efficiency. These endplates were allocated into groups A, B, and C, according to their Modic changes. Group A had endplates with type 2 Modic change and endplate sclerosis. Group B had type 2 Modic change without endplate sclerosis. Group C had neither Modic change nor endplate sclerosis. The presence of Modic change was determined by magnetic resonance imaging (MRI). Endplate sclerosis in type 2 Modic change was detected by computed tomography (CT) before the operation. We collected CT data 3 months to more than 24 months after operation in patients to assess bony fusion. RESULTS: Incidences of bony fusion were 58.8% in group A, 95.0% in group B, 94.3% in group C. The bony fusion rate was significantly lower in group A than in either group B or C. There was no significant difference between groups B and C. Thus, endplates with type 2 sclerotic Modic change had a lower fusion rate in patients undergoing PLIF with PSI. CONCLUSION: Type 2 sclerotic Modic change could be an important factor that affects solid bony fusion in patients undergoing PLIF with PSI. CT may help diagnose endplate sclerosis in patients with type 2 change and inform the choice of the best site for spinal fusion.

Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma.

Melanoma is a skin cancer with great metastatic potential, which is responsible for the major deaths in skin cancer. Although the prognosis of melanoma patients has been improved with the comprehensive treatment, for patients with metastasis, the complexity and heterogeneity of diffuse diseases make prognosis prediction and systematic treatment difficult and ineffective. Therefore, we established a novel personalized immune-related gene pairs index (IRGPI) to predict the prognosis of patients with metastatic melanoma, which was conducive to provide new insights into clinical decision-making and prognostic monitoring for metastatic melanoma. Through complex analysis and filtering, we identified 24 immune-related gene pairs to build the model and obtained the optimal cut-off value from receiver operating characteristic curves, which divided the patients into high and low immune-risk groups. Meantime, the Kaplan-Meier analysis, Cox regression analysis and subgroup analysis showed that IRGPI had excellent prognostic value. Furthermore, IRGPI was shown that was closely associated with immune system in the subsequent tumor microenvironment analysis and gene set enrichment analysis. In addition, we broken through the data processing limitations of traditional researches in different platforms through the application of gene pairs, which would provide great credibility for our model. We believe that our research would provide a new perspective for clinical decision-making and prognostic monitoring in metastatic melanoma.