Table 3.

Feature importance, macro area under receiver operating characteristic curves (macro-AUC), and optimal thresholds of the synovial features in distinguishing OA and RA patients

Feature	Feature importancea	macro-AUC	Optimal threshold OA vs RAb
Mast cells	0.34	0.80	Present vs none
Automated cell density	0.25	0.88	<3400c cells/mm2
Fibrosis	0.11	0.84	Focal and widespread vs none
Lining hyperplasia	0.10	0.78	Normal lining or 2–3 cells thick vs >3–4 cells thick or > 4 cells thick
Fibrin	0.05	0.68	None vs present
Sub-lining giant cells	0.05	0.57	None vs present
Lymphocytic inflammation	0.04	0.69	None and mild (0–1 perivascular aggregates per low power field) vs marked (both perivascular and widespread interstitial aggregates) and band-like
Neutrophils	0.02	0.60	None vs present
Detritus	0.01	0.64	Absent vs present (small or large particles)
Plasma cells	0.01	0.66	<50% plasma cells
Binucleate plasma cells	0.01	0.60	None vs present
Synovial giant cells	0.01	0.58	None vs present
Germinal centers	0.01	0.51	None vs present
Mucoid change	0.00	0.50	No optimal threshold
Russell bodies	0.00	0.56	None vs present

macro-AUC macro area under the receiver operating curve

^aFeature importance scores represent scores for the supervised machine learning model including all fourteen pathology scores and the computer vision-generated cell density

^bSee the Appendix for a full list of categorical variables

^cComputer vision-quantified cell density measured in mean cells per mm² of tissue