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. Author manuscript; available in PMC: 2020 Nov 4.
Published in final edited form as: Am J Drug Alcohol Abuse. 2020 Mar 16;46(5):531–545. doi: 10.1080/00952990.2020.1712410

Table 5.

USAUDIT and USAUDIT-C cutoff score analysis in the overall sample and by gender.

Overall Sample Males Females
Score Sensitivity Specificity J PPV NPV Sensitivity Specificity J PPV NPV Sensitivity Specificity J PPV NPV
USAUDIT
1 1.000 .004 .004 .399 1.000 1.000 .015 .015 .421 1.000
2 .987 .087 .074 .417 .909 .980 .060 .040 .427 .807 .990 .099 .089 .407 .941
3 .974 .196 .170 .445 .918 .980 .134 .114 .447 .904 .970 .222 .192 .437 .922
4 .961 .326 .287 .485 .926 .980 .269 .249 .490 .950 .950 .352 .302 .478 .919
5 .914 .461 .375 .529 .891 .940 .433 .373 .543 .910 .901 .475 .376 .517 .885
6 .829 .565 .394 .558 .833 .940 .507 .447 .577 .922 .772 .586 .358 .538 .805
7 .776 .717 .493 .645 .829 .880 .567 .447 .592 .869 .723 .778 .501 .670 .818
8 .717 .796 .513 .699 .810 .840 .597 .437 .599 .839 .653 .877 .530 .768 .802
9 .645 .839 .484 .726 .781 .740 .687 .427 .628 .787 .594 .901 .495 .789 .781
10 .566 .874 .440 .748 .753 .720 .761 .481 .683 .792 .485 .920 .405 .791 .741
11 .487 .904 .391 .771 .727 .640 .806 .446 .702 .758 .406 .944 .350 .819 .718
12 .428 .935 .363 .813 .712 .620 .866 .486 .768 .761 .327 .963 .290 .846 .697
13 .375 .948 .323 .826 .696 .560 .881 .441 .771 .737 .287 .975 .262 .877 .687
14 .309 .961 .270 .839 .678 .500 .896 .396 .775 .715 .218 .988 .206 .919 .670
15 .283 .978 .261 .896 .674 .440 .955 .395 .875 .705 .208 .988 .196 .915 .667
USAUDIT-C
1 1.000 .009 .009 .400 1.000 1.000 .015 .015 .421 1.000 1.000 .006 .006 .385 1.000
2 .954 .104 .058 .413 .774 .960 .090 .050 .430 .759 .950 .111 .061 .400 .781
3 .914 .243 .157 .444 .810 .920 .194 .114 .449 .772 .911 .265 .176 .436 .827
4 .875 .391 .266 .487 .826 .900 .343 .243 .495 .827 .861 .414 .275 .478 .827
5 .829 .509 .338 .527 .818 .880 .463 .343 .540 .844 .802 .531 .333 .516 .811
6 .697 .678 .375 .589 .772 .860 .567 .427 .587 .850 .614 .722 .336 .579 .750
7 .612 .787 .399 .655 .754 .760 .627 .387 .593 .785 .535 .852 .387 .693 .746
8 .454 .865 .319 .690 .706 .600 .687 .287 .578 .706 .386 .938 .324 .795 .710
9 .342 .917 .259 .731 .678 .480 .806 .286 .639 .684 .277 .963 .240 .824 .681
10 .250 .952 .202 .775 .658 .420 .896 .316 .743 .684 .168 .975 .143 .807 .653

Optimal cutoff scores are shaded in gray and interpreted as “greater than or equal to” a given value.