ObjectivesTo systematically review the association between the variants of HNF1B gene and the risk of prostate cancer.MethodsPubMed, EMbase, The Cochrane Library, CNKI, CBM and WanFang Data databases were electronically searched to collect case-control studies on the association between the variants of HNF1B gene and risk of prostate cancer from inception to December, 2017. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Meta-analysis was then performed using Stata 14.0 software.ResultsA total of 15 case-control studies involving 30 532 patients and 38 832 controls were included. The results of meta-analysis showed that: there was a strong significant association between rs4430796 variants (Gvs.A: OR=0.802, 95%CI 0.784 to 0.821, P<0.001; GGvs.AA: OR=0.659, 95%CI 0.606 to 0.717, P<0.001; AGvs.AA: OR=0.762, 95%CI 0.714 to 0.814, P<0.001), rs11649743 variants (Avs.G: OR=0.875, 95%CI 0.820 to 0.941, P<0.001; AAvs.GG: OR=0.669, 95%CI 0.564 to 0.792, P<0.001; AGvs.GG: OR=0.855, 95%CI 0.798 to 0.916, P<0.001), rs7501939 variants (Avs.G: OR=0.833, 95%CI 0.807 to 0.859, P<0.001), rs3760511 variants (Avs.C: OR=0.834, 95%CI 0.803 to 0.868, P<0.001) and risk of prostate cancer.ConclusionsCurrent evidence shows that HNF1B gene variants are associated with risk of prostate cancer. Due to limited quantity and quality of the included studies, more high quality studies are required to verify the above conclusion.
With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.
