background: Effective and accurate screening of oncological biomarkers in peripheral blood circulation plays an increasingly vital role in diagnosis and prognosis. High-sensitivity assays can effectively aid clinical decision-making and intervene in cancer in a localized status before they metastasize and become unmanageable. Meanwhile, it is equally pivotal to prevent overdiagnosis of non-life-threatening cancer by eliminating unnecessary treatment and repeated blood draws. Unfortunately, current clinical screening methodologies can hardly simultaneously attain sufficient sensitivity and specificity, especially under resource-restrained circumstances. To circumvent such limitations, particularly for cancer biomarkers from early-onset and recurrence, we aim to develop a universal plasmonic platform for clinical applications, which macroscopically amplifies multiplexed fluorescence signals in a broad spectral window and readily adapts to current assay setups without sophisticated accessories or expertise at low cost. methods: The plasmonic substrate was chemically synthesized in situ at the solid-liquid interface by rationally screening a panel of reducing monosaccharides and tuning the redox reactions at various catalyst densities and precursor concentrations. The redox properties were studied by Benedict's assay and electrochemistry. We systemically characterized the morphologies and optical properties of the engineered plasmonic Ag structures by scanning electron microscopy (SEM) and spectroscopy. The structure-fluorescence enhancement correlation was explicitly explained by the finite-difference time-domain (FDTD) simulation and a computational model for gap distribution. Next, we established an enhanced fluoroimmunoassay (eFIA) using a model biomarker for prostate cancer (PCa) and validated it in healthy and PCa cohorts. Prognosis was explored in patients subject to surgical and hormonal interventions following recommended PCa guidelines. results: The monosaccharide-mediated redox reaction yielded a broad category of Ag structures, including sparsely dispersed nanoparticles (NPs) of various sizes, semi-continuous nanoislands, and crackless continuous films. Optimal broad-spectral fluorescence enhancement from green to far-red was observed for the inhomogeneous, irregularly-shaped semi-continuous Ag nanoisland substrate (AgNIS), synthesized from a well-balanced redox reaction at a stable rate mediated by mannose. In addition, different local electric field intensity distributions in response to various incident excitations were observed at the nanoscale, elucidating the need for irregular and inhomogeneous structures. AgNIS enabled a maximized 54.7-fold macroscopically amplified fluorescence and long-lasting photostability. Point-of-care availability was fulfilled using a customized smartphone prototype with well-paired optics. The eFIA effectively detected the PCa marker in cell lines, xenograft tumors, and patient sera. The plasmonic platform rendered a diagnostic sensitivity of 86.0% and a specificity of 94.7% and capably staged high-grade PCa that the clinical gold standard test failed to stratify. Patient prognosis of robotic-assisted surgeries and hormone therapies was non-invasively monitored following efficient medical interventions. The assay time was significantly curtailed on the plasmonic platform upon microwave irradiation. conclusions: By investigating the effects of reducing monosaccharides on the seed-mediated chemical synthesis of plasmonic Ag structures, we deduced that potent multiplexed fluorescence enhancement originated from both an adequate reducing power and a steady reduction rate. Furthermore, the inhomogeneous structure with adequate medium gap distances afforded optimal multiwavelength fluorescence enhancement, thus empowering an effective eFIA for PCa. The clinically validated diagnostic and prognostic features, along with the low sample volume, point-of-care feasibility with a smartphone, and microwave-shortened assay time, warrant its potential clinical translation for widespread cancer biomarker analysis.