Objective. The aim of this study is to compare Parkinson’s disease (PD) treatment practices by movement disorder (MD) specialists across a decade, and to determine the factors that influence drug choice for the motor symptoms of PD in newly diagnosed drug-naïve patients. Methods. This prospective temporal analysis included patients seen at the National Neuroscience Institute in Singapore and diagnosed with PD by MD specialists in the years 2007 and 2017. Primary outcomes were use of specific PD drugs and changes in drug-prescribing patterns. Descriptive analyses and multivariable logistic regression models determined the extent to which patient characteristics were associated with type of PD treatment. Results. Of 230 patients with PD (mean (SD) age, 66.7 (10.3) years), 131 (57.0%) were male. From 2007 to 2017, the use of ergot dopamine agonists and anticholinergics decreased from 19.3% to 2.0% (P<0.001) and from 12.0% to 2.7% (P=0.004), respectively. The use of monoamine oxidase B inhibitors (MAOBI) increased from 13.3% to 25.2% (P=0.033). The use of levodopa (LD)-sparing strategies decreased nonsignificantly from 33.7% to 24.5% (P=0.133). Overall, 196 (85.2%) patients were initiated on symptomatic monotherapy, with LD being the most commonly prescribed. MAOBI was the most common drug used in combination therapy. Age ≤70 (adjusted OR, 11.9; 95% CI, 4.5–31.5) and Hoehn and Yahr (HY) stage <2 (adjusted OR, 3.4; 95% CI, 1.5–7.7) were independent factors for LD-sparing strategies. Non-LD prescriptions (13 of 92; 14.1%) were more likely to be discontinued compared to LD ones (6 of 149; 4.0%) (P=0.005). Conclusions. Drug-prescribing patterns in PD have changed significantly through the last decade, influenced by emerging evidence and reports of adverse drug effects. Choosing drugs based on the patient’s age and disease severity remain sound guiding principles across the years. It is important that international and national guidelines for pharmacotherapy in PD be updated consistently throughout different socioeconomic settings to optimize care.