Effects of teriparatide versus alendronate for treatment of postmenopausal osteoporosis: A meta-analysis of randomized controlled trials.

OBJECTIVES: Osteoporosis remains a clinical challenge. Teriparatide is an anabolic drug and alendronate is an antiresorptive agent; both are used in the treatment of osteoporosis. Comprehensive reviews investigating the comparative safety and efficacy of teriparatide versus alendronate are scarce. Therefore, we conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the safety and efficacy of teriparatide versus alendronate for the treatment of postmenopausal osteoporosis. METHODS: We conducted a comprehensive literature review of the PubMed, EMBASE, Cochrane Controlled Trials Registry, and the China Academic Journal Network Publishing databases for relevant RCTs of teriparatide versus alendronate in postmenopausal osteoporosis patients. Outcome measures were percentage change in lumbar spine and femoral neck bone mineral density (BMD) and incidence of vertebral and nonvertebral fractures. Effect size was reported as weighted mean differences (WMDs) for continuous outcomes and odds ratios (OR) for dichotomous outcomes, with associated 95% confidence intervals (CIs). RESULTS: Six trials involving 618 patients were included. The meta-analysis demonstrated a significant increase in lumbar spine BMD (WMD: 3.46, 95% CI: 2.15-4.77, P < .00001), but not femoral neck BMD (WMD = 1.50, 95% CI: 0.04-2.95, P = .04), in postmenopausal osteoporosis patients treated with teriparatide compared with alendronate for 6 to 18 months. These beneficial effects were apparent in the lumbar spine at 12 months of treatment (WMD: 4.49, 95% CI: 2.57-6.40, P < .01). Teriparatide was not superior to alendronate in reducing fracture risk (OR: -0.03, 95% CI: -0.12 to 0.07; P = .52). CONCLUSION: Teriparatide may be superior to alendronate for increasing lumbar spine BMD in postmenopausal osteoporosis. The efficacy and safety of long-term teriparatide and alendronate treatment in postmenopausal osteoporosis should be further investigated in clinical trials.

MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain.

BACKGROUND: The identification of the cause of chronic low back pain (CLBP) represents a great challenge to orthopedists due to the controversy over the diagnosis of discogenic low back pain (DLBP) and the existence of a number of cases of CLBP of unknown origin. This study aimed to develop diagnostic models to distinguish DLBP from other forms of CLBP and to identify serum biomarkers for DLBP. METHODS: Serum samples were collected from patients with DLBP, chronic lumbar disc herniation (LDH), or CLBP of unknown origin, and healthy controls (N), and randomly divided into a training set (n = 30) and a blind test set (n = 30). Matrix-assisted laser desorption ionization time-of-flight mass spectrometry was performed for protein profiling of these samples. After the discriminative ability of two most significantly differential peaks from each two groups was assessed using scatter plots, classification models were developed using differential peptide peaks to evaluate their diagnostic accuracy. The identity of peptides corresponding to three representative differential peaks was analyzed. RESULTS: The fewest statistically significant differential peaks were identified between DLBP and CLBP (3), followed by CLBP vs. N (5), DLBP vs. N (9), LDH vs. CLBP (20), DLBP vs. LDH (23), and LDH vs. N (43). The discriminative ability of two most significantly differential peaks was poor in classifying DLBP vs. CLBP but good in classifying DLBP vs. LDH. The accuracy of models for classification of DLBP vs. CLBP was not very high in the blind test (forecasting ability, 67.24%; sensitivity, 70%), although a higher accuracy was observed for classification of DLBP vs. LDH and LDH vs. N (forecasting abilities, ~90%; sensitivities, >90%). A further investigation of three representative differential peaks led to the identification of two peaks as peptides of complement C3, and one peak as a human fibrinogen peptide. CONCLUSIONS: Our findings benefit not only the diagnosis of CLBP but also the understanding of the differences between different forms of DLBP. The ability to distinguish between different causes of CLBP and the identification of serum biomarkers may be of great value to diagnose different causes of DLBP and predict treatment efficacy.