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Interpreting Statistics in the Urological Literature

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Presentation on theme: "Interpreting Statistics in the Urological Literature"— Presentation transcript:

1 Interpreting Statistics in the Urological Literature
Charles D. Scales, Bercedis Peterson, Philipp Dahm  The Journal of Urology  Volume 176, Issue 5, Pages (November 2006) DOI: /j.juro Copyright © 2006 American Urological Association Terms and Conditions

2 Fig. 1 Histograms show hypothetical distributions. Of 2 histograms with normal distributions (A and B) 1 appears more normal (A) only because sample size is larger. Asymmetrical distribution is said to be skewed to right (C). Bimodal distribution has high point at around age 35 years and another at around age 65 years (D). The Journal of Urology  , DOI: ( /j.juro ) Copyright © 2006 American Urological Association Terms and Conditions

3 Fig. 2 PLESS results27 The Journal of Urology  , DOI: ( /j.juro ) Copyright © 2006 American Urological Association Terms and Conditions

4 Fig. 3 Hypothetical example shows how odds and probabilities of dying (filled circles) vs not dying (open circles) of prostate cancer are calculated. In several hypothetical series of 20 patients differing in number of cancer related deaths, as long as event rate is low (Series #1 and #2), calculated odds and probabilities are similar. With increasing event rates odds and probabilities diverge. Probabilities of 0.5 and 0.75, ie 50% and 75% of patients dying of prostate cancer (Series #4 and #5), correspond to odds of 1 and 3, respectively. Odds can be calculated from probabilities and vice versa. The Journal of Urology  , DOI: ( /j.juro ) Copyright © 2006 American Urological Association Terms and Conditions

5 Fig. 4 Hypothetical survival curve compares 2 groups of patients with renal cell carcinoma, including time to death in 15 each with node negative (solid curve) and node positive (dotted curve) disease. In node negative group first patient dies after 12 months. At that point all patients in that group are still followed and curve drops by 1/15 to 0.93, ie 1.0 – Second patient dies after 25 months, at which time 5 in that group have been censored (vertical tick marks). Since only 9 patients are followed at that point, death of 1 patient causes curve to drop by 1/9 from 0.93 to 0.82, ie 0.93 – Survival curve then continues horizontally. No further patient dies and additional 8 are censored for total of 13 censored. In node positive group 7 patients die and each causes survival curve to drop to relatively greater extent due to smaller number followed. Median survival time in node positive group is calculated as 25 months, whereas it cannot be calculated in node negative group since fewer than half of patients are dead at study end. The Journal of Urology  , DOI: ( /j.juro ) Copyright © 2006 American Urological Association Terms and Conditions


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