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Volume 11, Number 8—August 2005

Research

Optimizing Treatment of Antimicrobial-resistant Neisseria gonorrhoeae

Kakoli Roy*Comments to Author , Susan A. Wang*, and Martin I. Meltzer*
Author affiliations: *Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Main Article

Table 5

Monte Carlo simulation* results: mean cost per patient treated and percentage of patients without PID† >(5th percentile, 95th percentile)

Prevalence (%) gonorrhea Strategy‡ Prevalence of ciprofloxacin resistance = 0.1%
Prevalence of ciprofloxacin resistance = 2%
$/patient treated % patients without PID $/patient treated % patients without PID
1 ST1 27.34
(21.45, 33.23) 99.92
(99.84, 99.96) 27.44
(21.72, 33.64) 99.92
(99.84, 99.96)
ST2 39.78
(30.45, 50.19) 99.92
(99.83, 99.96) 39.78
(30.57, 50.95) 99.92
(99.84, 99.96)
ST3 28.94
(22.92, 35.08) 99.92
(99.84, 99.96) 28.99
(23.25, 35.32) 99.92
(99.84, 99.96)
ST4 42.00
(31.38, 53.08) 99.93
(99.84, 99.96) 41.99
(32.23, 53.83) 99.92
(99.84, 99.96)
10 ST1 68.73
(46.22, 99.01) 99.18
(98.41, 99.59) 71.65
(47.04, 102.58) 99.16
(98.38, 99.61)
ST2 77.34
(53.53, 106.86) 99.23
(98.43, 99.63) 77.29
(54.83, 110.64) 99.19
(98.44, 99.61)
ST3 70.37
(47.06, 98.72) 99.18
(98.41, 99.60) 70.33
(46.85, 101.75) 99.17
(98.39, 99.61)
ST4 79.69
(55.78, 109.48) 99.23
(98.44, 99.80) 79.68
(55.90, 110.87) 99.21
(98.48, 99.63)

*Monte Carlo simulation involves specifying a probability distribution of values for model inputs (see Tables 2 and 3 for distributions used). A computer algorithm ran the model for 10,000 iterations. During each iteration, the computer algorithm selects input values from the probability distributions and calculates the output (e.g., cost per patient successfully treated). After the final run, the model provides results such as the mean, median, and 5th and 95th percentiles for each specified output.
†PID, pelvic inflammatory disease, which can cause sequelae such as chronic pelvic pain, infertility, and ectopic pregnancy.
‡The strategies modeled were ST1: ciprofloxacin + culture-based tests + ciprofloxacin-susceptibility tests; ST2: ciprofloxacin + nonculture-based tests; ST3: ceftriaxone + culture-based tests + ceftriaxone-susceptibility tests; ST4: ceftriaxone + nonculture-based tests. See Table 1 and text for further details.

Main Article

1In 2000, only 18% of gonorrhea tests performed by public health laboratories in the United States were culture-based tests.

2Monte Carlo simulation involves specifying a probability distribution of values for model inputs. A computer algorithm then runs the model for several iterations. During each iteration, the computer algorithm selects input values from the probability distributions, and calculates the output (e.g., cost per patient successfully treated). After the final run, the model provides results such as the mean, median, and 5th and 95th percentiles for each specified output.

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