Owing to their high sensitivity with respect to external measurands, Rayleigh-based distributed optical fiber sensors (DOFS) find their way into applications in many industrial and academic sectors. To further transcend the limit of these sensors in terms of sensing range, low spatial resolution, speed and accuracy of the measurement, improving the signal-to-noise ratio (SNR) of the system plays a pivotal role. Out of the several existing techniques for enhancing the SNR, one such method, solely dedicated to the Rayleigh-based sensors, is through intrinsically increasing the backreflected signal of the fibers. The enhanced backreflected signal provided by such fibers, generally known as reflection-enhanced fibers (REF), is rigorously analyzed in the present work. It is inferred from the analysis that the enhanced signal is essentially accompanied by enhanced signal-dependent noises, which can adversely affect their performance. For instance, when a performance comparison is carried out between the REF and a standard single-mode fiber (SMF) under identical experimental conditions, due to their different intrinsic backreflected signal levels, the two fibers experience dissimilar noise regimes leading to an erroneous estimation of the performance of the former. This necessitates the optimization of the interrogation system and the experimental parameters while employing such fibers for specific sensing applications. Additionally, a distributed temperature measurement is presented by taking advantage of the enhanced SNR of a 100 m long REF exhibiting a sub-mK temperature uncertainty of 0.5 mK at metric spatial resolution yielding a sixfold improvement compared to the 3 mK uncertainty of an SMF.