Objective To explore the relevances of serum prolactin level to clinical symptoms and disease activities of systemic lupus erythematosis (SLE). Methods From December 2008 to December 2014, 63 female patients who met the American Rheumatism Society diagnostic criteria of SLE in the First People’s Hospital of Chengdu were collected as the SLE group, and other 20 healthy females were collected as the control group. The serum prolactin level was determined by immunofluorescence, and the disease activity of SLE was assessed by SLE Disease Activity Index (SLEDAI). The relevances of serum prolactin level to clinical symptoms and disease activity of SLE patients were analyzed. Results The mean serum prolactin level was (22.35±14.86) ng/mL in the SLE group and (15.30±8.54) ng/mL in the control group, respectively; the difference was statistically significant (P<0.05). In the 63 SLE patients, 15 (23.8%) had higher serum prolactin level compared with the normal ones. According to the SLEDAI score, the SLE patients were divided into stable group (25 patients), mild activity group (21 patients), moderate activity group (10 patients), and severe activity group (7 patients); and their serum prolactin levels were (20.43±11.23), (22.50±13.54), (27.97±21.20), and (33.91±18.18) ng/mL, respectively; the differences were not statistically significant (P>0.05). There were statistically significant differences (P<0.05) between the SLE patients with hyperprolactinemia and the ones with normal serum prolactin level in a number of clinical symptoms such as serositis, kidney damage,hematological system damage, and hypocomplementemia, but the serum prolactin level was not significantly correlated with the SLEDAI (rs=0.217, P=0.088). Conclusions Less hyperprolactinemia is found in SLE patients. Serum prolactin level is correlated with multiple clinical symptoms and laboratory indexes but not related to disease activity in SLE patients.
The treatment goal for acromegaly has shifted from just hitting biochemical targets of growth hormone (GH) and insulin-like growth factor-1 (IGF-1) remission to a long-term, comprehensive improvement that also considers hormones, metabolic regulations, tumor, symptoms, comorbidities, and patient experience. The SAGIT? assessment system, as the first multi-dimensional clinician-reported outcome tool, integrates five aspects: signs and symptoms (S), associated comorbidities (A), GH levels (G), IGF-1 levels (I), and tumor profile (T). It enables quantitative scoring and dynamic stratification of disease severity. International prospective validation studies have shown that each SAGIT? dimension has good discriminatory ability for disease control; a 2025 multicenter study indicated that SAGIT? objectively reflects disease activity. This article systematically reviews the limitations of existing assessment tools, explains the design principles and scoring criteria of SAGIT?, and discusses its clinical value in disease staging, treatment decision-making, efficacy prediction, and follow-up management. Furthermore, it explores future directions for improving SAGIT? and other disease rating tools, including artificial intelligence integration, development of dynamic monitoring modules, and validation and application in Chinese patients with acromegaly.