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Objective: The substantial prevalence of nonadherence to analgesic medication among individuals diagnosed with cancer imposes a significant strain on both patients and healthcare resources. The objective of this study is to develop and authenticate a nomogram model for assessing nonadherence to analgesic medication in cancer patients. Methods: Clinical information, demographic data, and medication adherence records of cancer pain patients were gathered from the Affiliated Hospital of Chengde Medical University between April 2020 and March 2023. The risk factors associated with analgesic medication nonadherence in cancer patients were analyzed using the least absolute selection operator (LASSO) regression model and multivariate logistic regression. Additionally, a nomogram model was developed. The bootstrap method was employed to internally verify the model. Discrimination and accuracy of the nomogram model were evaluated using the Concordance index (C-index), area under the receiver Operating characteristic (ROC) curve (AUC), and calibration curve. The potential clinical value of the nomogram model was established through decision curve analysis (DCA) and clinical impact curve. Results: The study included a total of 450 patients, with a nonadherence rate of 43.33%. The model incorporated seven factors: age, address, smoking history, number of comorbidities, use of nonsteroidal antiinflammatory drugs (NSAIDs), use of opioids, and PHQ-8. The C-index of the model was found to be 0.93 (95% CI: 0.907-0.953), and the ROC curve demonstrated an AUC of 0.929. Furthermore, the DCA and clinical impact curves indicate that the built model can accurately predict cancer pain patients' medication adherence performance. Conclusions: A nomogram model based on 7 risk factors has been successfully developed and validated for long-term analgesic management of cancer patients.
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@#Objective: To investigate the expression of lncRNA01296 in esophageal cancer (EC) tissues and its effect on the proliferation and migration of EC TE-2 cells. Methods:Atotal of 36 pairs of esophageal cancer tissues and corresponding para-cancerous tissues were collected from EC patients admitted to the Department of Thoracic Surgery,Affiliated Hospital of Chengde Medical College from January 2017 to September 2018. The human normal esophageal epithelial (HEEC) cells and human esophageal cancer cell lines ECA109, TE-1 and TE-2 were cultured. qPCR was used to detect the mRNAexpressions of lincRNA01296, SNRPA(small nuclear ribonucleoproteinA) and NGF (nerve growth factor) in EC tissues and cells. Recombinant lentiviral interference vectoror control vector were used to transfect EC cell lines, as sh-lncRNA01296#1,#2 and Mock groups. WB was used to detect the protein expressions of SNRPAand NGF in transfected cells. MTS assay was used to detect cell proliferation, and Transwell assays were used to detect cell invasion and migration of TE-2 cells after transfection. Results: The mRNAexpressions of lncRNA01296, SNRPAand NGF were significantly increased in esophageal cancer tissues and cell lines (all P<0.01), and these expressions in poorly differentiated TE-2 cells were higher than those in highly differentiated ECA109 and TE-1 cells (all P<0.05). The mRNAexpressions of lncRNA01296 and NGF in sh-lncRNA01296#1 and sh-lncRNA01296#2 groups were significantly lower than those in Mock group (all P<0.01), while the mRNAexpression of SNRPAshowed no statistical difference among three groups (P>0.05). The protein expressions of lncRNA01296 and NGF in sh-lncRNA01296#1 and sh-lncRNA01296#2 groups were significantly lower than those in Mock group (all P<0.01). The relative proliferation ability of cells in sh-lncRNA01296#1 and shlncRNA01296#2 groups was significantly lower than that of Mock group at 48 and 72 h after transfection (P<0.05 or P<0.01). The number of invasive cells was (72.0±6.3), (36.6±4.3) and (33.9±3.7) in Mock, sh-lncRNA01296#1 and sh-lncRNA01296#2 groups, respectively; and the number of migrated cells was (85.2±9.9), (47.5±8.1) and (43.8±6.5), respectively, indicating that the numbers of invasive and migrated cells in sh-lncRNA01296#1 and sh-lncRNA01296#2 groups were significantly less than those in Mock group(all P<0.01). Conclusion: lncRNA01296 can up-regulate SNRPAexpression to promote NGF-mediated proliferation and metastasis of EC cells, which may provide new target for the diagnosis and treatment of esophagealcancer.
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BACKGROUND: Ribonucleotide reductase subunit 1 (RRM1) is a potential prognostic factor for non-small cell lung cancer (NSCLC). This study evaluates prognostic value of RRM1 in NSCLC patients by meta-analyzing outcomes reported in literature. METHOD: Data were acquired from research articles retrieved after literature search in online databases. Random effects meta-analyses were conducted by pooling hazard ratios (HR). Meta-analyses of standardized mean differences (SMD) were used to evaluate overall survival (OS) and progression-free survival (PFS) between low and high RRM1 expression groups. Metaregression analyses were conducted to evaluate the factors that could affect prognostic relationship of RRM1 with treatment and survival outcomes. RESULTS: 23 studies (3148 patients) were included. RRM1 expression was not meaningfully associated with prognosis of NSCLC even when the reference (HRâ¯=â¯1) was either low RRM1 expression (0.918 [95% CI 0.833, 1.003]) or high RRM1 expression (0.834 [0.625, 1.043]). OS was significantly longer in low RRM1 expression group compared to high RRM1 expression group (SMD 0.73 [0.36, 1.09]; Pâ¯<â¯0.0001). PFS was not significantly different between low and high RRM1 expression groups (SMD 0.08 [-0.29, 0.45]; pâ¯=â¯0.68). Age was inversely associated with HR (pâ¯=â¯0.001) even when reference was low RRMI (pâ¯=â¯0.027) or high RRM1 (pâ¯=â¯0.006). Age was positively associated with OS in both low and high RRM1 groups. CONCLUSION: In meta-analysis of studies which used gemcitabine-based therapies, higher RRM1 expression is found to associated with shorter OS but not PFS. HR depicting relationship between RRM1 expression and OS/PFS/treatment response could not demonstrate a prognostic role of RRM1 in NSCLC patients.
