Serum levels of insulin-like growth factor I (IGF-I), IGF-II, IGF-binding protein-3, and prostate-specific antigen as predictors of clinical prostate cancer.

Insulin-like growth factors (IGFs) may play a role in prostate growth, hyperplasia, and malignancy. High plasma IGF-I has been associated with increased prostate cancer risk. In a prospective, cohort, case-control study in the Baltimore Longitudinal Study on Aging population, we examined prostate volume by magnetic resonance imaging, and prostate-specific antigen (PSA), IGF-I, IGF-II, and IGF-binding protein-3 (IGFBP-3) in sera obtained approximately 9 yr before diagnosis of prostate cancer in cases (n = 72) or age-matched controls (n = 127) and in 76 additional Baltimore Longitudinal Study on Aging men (normal subjects) with measured prostate volumes and no prostate cancer. We calculated adjusted odds ratios (OR) by logistic regression, relative risks for significant ORs, and receiver operator curves for prostate cancer, using serum measures alone and in combination. Adjusted ORs for the high vs. low tertile were: for IGF-I, 3.1 [confidence interval (CI), 1.1-8.7]; for IGF-II, 0.2 (CI, 0.07-0.6); for IGFBP-3, 0.71 (CI, 0.3-1.7); and for PSA, 12.5 (CI, 3.8-40.9). For significant ORs, relative risk estimates remained significant at 2.0 for IGF-I, 0.3 for IGF-II, and 5.5 for PSA. Receiver operator curves showed PSA to be the most powerful predictor of prostate cancer. Adding IGF-II to PSA improved prediction. IGF-II was significantly and inversely related (r = -0.219; P < 0.01) and PSA was directly and significantly related (r = 0.461; P < 0.0001) to prostate volume, whereas IGF-I and IBFBP-3 were not. High IGF-I and low IGF-II are independently associated with increased risk of prostate cancer, but PSA level is a much stronger predictor of prostate cancer in the ensuing 10 yr than either IGF-I or IGF-II. The absence of a relationship of IGF-I to prostate size is inconsistent with increased ascertainment in men with large prostates as the source of greater prostate cancer risk associated with IGF-I. Our data suggest that IGF-II may inhibit both prostate growth and development of prostate cancer.

Prostate-specific antigen testing of older men.

BACKGROUND: Elevated serum prostate-specific antigen (PSA) levels are predictive of a future diagnosis of prostate cancer. To test the hypothesis that older men with low PSA levels may require less intensive PSA testing because of a reduced prostate cancer detection rate, we evaluated the association between age, baseline PSA level, and prostate cancer detection. METHODS: We conducted a prospective cohort study among participants in a study of aging who had serial PSA measurements taken from age 60 or 65 years until they either were diagnosed with prostate cancer (cancer case subjects) or reached the age of 75 years (subjects without prostate cancer). The time of cancer detection among cancer case subjects was defined as the measurement date on which a PSA level above 4.0 ng/mL was detected (i.e., PSA conversion). Cancer case subjects and subjects without prostate cancer were analyzed according to baseline PSA level and age. RESULTS: All cancer case subjects in the 60-year-old cohort had baseline PSA levels above 0.5 ng/mL, and 14 of 15 cancer cases that would have been detected by a PSA conversion among the 65-year-old cohort were associated with baseline PSA levels of 1.1 ng/mL or more. If PSA testing were discontinued in men aged 65 years with PSA levels of 0.5 ng/mL or less, 100% (95% confidence interval [CI] = 78%-100%) of the cancers would still be detected by age 75 years; if PSA testing were discontinued in men aged 65 years who had PSA levels of 1.0 ng/mL or less, 94% (95% CI = 70%-100%) of the cancers would still be detected by age 75 years. CONCLUSIONS: These data suggest that a decrease in the intensity of screening among older men with low PSA values may not lead to an increase in undetected prostate cancer.

Prostatic growth rate determined from MRI data: age-related longitudinal changes.

Men with prostatic enlargement are at highest risk of developing symptomatic lower urinary tract symptoms (LUTS) and related outcomes, such as acute urinary retention. The study of prostatic growth rate can identify the age range at which prostate growth peaks. Evaluation of the natural course of prostate growth requires repeated intraindividual volume measurements at time intervals sufficient to document growth. Our objective was to examine age-stratified prostate growth rates from men taking part in a longitudinal study of aging using magnetic resonance imaging (MRI) of the prostate. Sixty-four men (ages 30-71 years) enrolled in the Baltimore Longitudinal Study of Aging (BLSA) who had T2 pelvic MRIs taken approximately every 2 years were studied. Men were age stratified into four groups: <45, 45-55, 56-65, and >65 years old. Whole prostate and central gland (anatomically referred to as the transition zone) volumes were determined from the MRI images by a semi-automated image analysis program. Peripheral gland volumes were calculated as the difference between whole prostate and central gland volumes. Growth rates (cc per year) were calculated as change in volume divided by the time interval. On the basis of measurements from the T2 images (n = 128), we observed a linear trend between prostate volume and age. The overall prostate growth rate was 2.36 +/- 3.52 cc per year. Age-stratified growth rates revealed that prostate growth increased with age, peaked at 4.15 +/- 4.98 cc/year for the 56-65-year-old age group and then declined rapidly for the older-aged men. The central gland growth rates followed a trend similar to total prostate volume. These data suggest that there is an age-related increase in prostate growth rate that peaks in men ages 56-65 and then declines. Identification of this trend in prostate growth may aid physicians in targeting men for early diagnosis of LUTS and for possible early intervention. Future studies with a larger sample size are necessary to substantiate these findings.

Age-associated changes in blood pressure in a longitudinal study of healthy men and women.

BACKGROUND: Current knowledge of age-associated increases in blood pressure is based primarily on unscreened population studies that may not be representative of healthy men and women. We examined longitudinal patterns of change in blood pressure in healthy male and female volunteers from the Baltimore Longitudinal Study of Aging (BLSA). METHODS: Longitudinal mixed-effects regression models are used to estimate the age-associated changes in blood pressure in 1307 men (age 17-97) and 333 women (age 18-93) who have been followed for up to 32 years (mean: 8.4 years for men and 3.4 years for women) and who have been screened for health problems or medications that affect blood pressure. RESULTS: On average, systolic pressure is relatively stable in men and women until approximately age 45, increases at 5-8 mm Hg per decade in middle age, then accelerates in men and stabilizes in women. Diastolic pressure increases at 1 mm Hg per decade at all ages in men, whereas in women the rate of change in diastolic pressure increases in middle age and then plateaus and may decline after age 70. Additional findings include: (a) BLSA cross-sectional and longitudinal findings are more similar than has been observed in studies of unscreened samples; (b) there is no evidence of a gender cross-over in this group of healthy men and women; and (c) compared to previous studies of unscreened samples, healthy BLSA men and women show a weaker association between baseline blood pressure and subsequent rate of blood pressure change. CONCLUSIONS: These findings suggest that several previously described age-associated patterns of blood pressure change partially reflect the effects of hypertension and its treatment, rather than intrinsic age changes in the blood pressure of healthy individuals.

Evaluation of serum prostate-specific antigen velocity after radical prostatectomy to distinguish local recurrence from distant metastases.

OBJECTIVE: Serum prostate-specific antigen (PSA) values are most useful for prediction of disease recurrence after surgery. It is unknown whether a detectable PSA level after surgery indicates a local recurrence potentially benefiting from pelvic irradiation or distant metastases requiring hormonal treatment. METHODS: We analyzed postoperative rate of change of serum PSA levels as a predictor of local versus distant disease recurrence after radical prostatectomy. Between 1982 and 1991, 1,058 men underwent radical prostatectomy for localized prostate cancer and follow-up consisted of determining serum PSA levels and digital rectal examinations. Clinical follow-up of 542 men for four or more years and 78 men for eight or more years yielded ten-year actuarial disease recurrence rates of 4 percent for local recurrence, 8 percent for distant metastases, and 23 percent for an isolated elevation of serum PSA level only. Fifty-one patients with isolated elevations of PSA levels only were followed expectantly until they were diagnosed with either local or distant metastases. RESULTS: A linear mixed effects regression analysis was used to model these data. Using these models, the time to a serum PSA level of 0.5 ng/mL, the PSA level one year following surgery, pathologic stage, Gleason sum, and the rate of change of PSA (PSA velocity [PSAV]) were tested as predictors of local versus distant metastases. A combination of PSAV, pathologic stage, and Gleason grade best distinguished local from distant metastases. CONCLUSIONS: These data suggest that PSAV in men with an isolated elevation of PSA levels following radical prostatectomy might aid in clinical decision making.

Mixed-effects regression models for studying the natural history of prostate disease.

Although prostate cancer and benign prostatic hyperplasia are major health problems in U.S. men, little is known about the early stages of the natural history of prostate disease. A molecular biomarker called prostate specific antigen (PSA), together with a unique longitudinal bank of frozen serum, now allows a historic prospective study of changes in PSA levels for decades prior to the diagnosis of prostate disease. Linear mixed-effects regression models were used to test whether rates of change in PSA were different in men with and without prostate disease. In addition, since the prostate cancer cases developed their tumours at different (and unknown) times during their periods of follow-up, a piece-wise non-linear mixed-effects regression model was used to estimate the time when rapid increases in PSA were first observable beyond the background level of PSA change. These methods have a wide range of applications in biomedical research utilizing repeated measures data such as pharmacokinetic studies, crossover trials, growth and development studies, aging studies, and disease detection.