Clinical likelihood ratios and balanced accuracy for 44 in silico tools against multiple large-scale functional assays of cancer susceptibility genes.

PURPOSE: Where multiple in silico tools are concordant, the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) framework affords supporting evidence toward pathogenicity or benignity, equivalent to a likelihood ratio of ~2. However, limited availability of "clinical truth sets" and prior use in tool training limits their utility for evaluation of tool performance. METHODS: We created a truth set of 9,436 missense variants classified as deleterious or tolerated in clinically validated high-throughput functional assays for BRCA1, BRCA2, MSH2, PTEN, and TP53 to evaluate predictive performance for 44 recommended/commonly used in silico tools. RESULTS: Over two-thirds of the tool-threshold combinations examined had specificity of <50%, thus substantially overcalling deleteriousness. REVEL scores of 0.8-1.0 had a Positive Likelihood Ratio (PLR) of 6.74 (5.24-8.82) compared to scores <0.7 and scores of 0-0.4 had a Negative Likelihood Ratio (NLR) of 34.3 (31.5-37.3) compared to scores of >0.7. For Meta-SNP, the equivalent PLR = 42.9 (14.4-406) and NLR = 19.4 (15.6-24.9). CONCLUSION: Against these clinically validated "functional truth sets," there was wide variation in the predictive performance of commonly used in silico tools. Overall, REVEL and Meta-SNP had best balanced accuracy and might potentially be used at stronger evidence weighting than current ACMG/AMP prescription, in particular for predictions of benignity.

Anthropometric correlates with strength performance among resistance trained athletes.

The purpose of this study was to determine the relationship between selected anthropometric dimensions and strength performance in resistance trained athletes. Fifty-eight college football players were measured following the completion of a 10-week resistance training program for one-repetition maximum (1-RM) lifts in the bench press, squat, and dead lift and for 11 anthropometric dimensions. Results indicated that the highest relationships existed between estimates of regional muscle mass (arm circumference, arm muscle cross-sectional area, and thigh circumference) and lifting performance. Multiple regression analysis selected arm size and %fat as variables common to the prediction of all three lifts. The fewer joints and muscle groups involved in a lift, the greater the predictive accuracy from structural dimensions. It was concluded that body structure and conformation make significant contributions to maximum strength performance in highly trained strength athletes.

Anthropometric and somatotype variables related to strength in American football players.

The purpose of this study was to investigate the differences in somatotype, % fat, and strength in relation to body mass of two groups of American football players. One hundred and forty-three football players (85 high school and 58 college) were classified into five weight groups (< 73 kg, 73-82 kg, 83-91 kg, 91-100 kg, > 100 kg). Body composition was estimated from skinfold, and somatotype was determined using the Heath-Carter method. Strength was measured from one-repetition maximum (1-RM) lifts in the bench press and deadlift. Most of the somatotypes were dominant mesomorphs for the high school player and endomesomorphs for the college player. The weight groups in both the high school and college footballer showed significant differences in % fat, somatotype, and strength measures between the lower and higher weight categories. Weight was a greater factor dictating strength in either lift in the high school player than in the college player. A higher mesomorphic component was a more important factor determining strength in the college player while a lower ectomorphic component contributed more in the high school player. The proportion of the variance accounted for by regression equations for the bench press and deadlift was 17% to 41% in the high school player and 35% to 61% in the college player. Although football requires a large individual at certain positions, the question remains concerning overall size versus muscularity to achieve a superior performance level.

Muscular endurance repetitions to predict bench press strength in men of different training levels.

The purpose of this study was to determine the accuracy of predicting maximal bench press (BP) strength (1-RM) from relative endurance performance in various groups of men. The subjects included untrained students (n = 35), resistance trained students (n = 28), college wrestlers (n = 21), soccer players (n = 22), football players (n = 51), high school students (n = 35), and resistance-trained middle-aged men (n = 24). Each subject performed a 1-RM test according to the same standard procedure. Within 4-10 days, the subject selected a weight to perform as many repetitions as possible to failure. Six relative endurance prediction equations produced validity coefficients of r = 0.86 to 0.98 in each group and r = 0.82 to 0.98 in the composite group (n = 220). In subjects completing < or = 10 repetitions-to-failure, three equations significantly overpredicted and two significantly underpredicted 1-RM scores. The Brzycki equation was the most accurate. In subjects completing > 10 repetitions to failure, three equations significantly overpredicted and three significantly underpredicted 1-RM scores. While caution should be used when employing relative muscular endurance performance to estimate 1-RM strength in the bench press, the average of two equations may reduce the error.

Validation of the NFL-225 test for predicting 1-RM bench press performance in college football players.

BACKGROUND: The purpose of this study was to evaluate the accuracy of repetitions-to-fatigue (RTF) using an absolute load of 102.3 kg (225 lbs) to estimate one-repetition maximum (1-RM) bench press performance in college football players using various prediction equations. EXPERIMENTAL DESIGN: a prospective study on the association between muscular endurance and muscular strength. PARTICIPANTS: 260 players from NCAA Division IA (n=43), IAA (n=63), II (n=129), and red-shirts (n=25) were evaluated at the conclusion of a minimum of eight weeks of heavy-resistance training during the off-season. MEASURES: all subjects performed a 1-RM bench press and RTF using an absolute load of 102.3 kg. RESULTS: The Mayhew et al. NFL-225 equation nonsignificantly overestimated 1-RM from RTF by 0.5 kg, while the Chapman et al. NFL-225 equation significantly underpredicted by 3.2 kg, although both equations were comparable in the number of players predicted within +/-4.5 kg of actual 1-RM (52% vs 51%, respectively). Only two of nine RTF equations currently in use produced predicted 1-RM values that were not significantly different from actual 1-RM performance. CONCLUSIONS: Specific NFL-225 equations are more accurate in estimating 1-RM bench press from absolute muscle endurance in college football players than previous published RTF equations. The accuracy of prediction decreases at higher repetitions.

Changes in upper body power following heavy-resistance strength training in college men.

The purpose of this study was to determine the effects of heavy-resistance strength training on measures of bench press power (BPP) using absolute loads and seated shot put (SSP) performance. Twenty-four college men were measured for 1-RM bench press, BPP, and SSP before and after weight training twice weekly for 12 weeks. BPP was measured with free weights using a digital timing system and randomly assigned loads equivalent to 30%, 40%, 50%, 60%, 70% and 80% of the 1-RM. Post-training tests used the same absolute loads as during the pre-training test to assess BPP. Following training BPP increased significantly at each load, shifting the power curve upward by an average of 13.6%. The 1-RM bench press increased significantly by 9.1%, but the SSP increased nonsignificantly by only 1.8%. Peak power was produced at approximately 40-50% of the 1-RM before and after training. Changes in SSP distance were nonsignificantly correlated (r=0.27-0.20) with the increases in BPP. Resistance training shifts the power curve in a positive direction when the measurements are determined with absolute loads, but the increased power may not be transferred to an absolute performance task like the SSP.