Refining the definition of biochemical failure in the era of stereotactic body radiation therapy for prostate cancer: The Phoenix definition and beyond

BACKGROUND AND PURPOSE

The Phoenix definition for biochemical failure (BCF) after radiotherapy uses nadir PSA (nPSA) + 2 ng/mL to classify a BCF and was derived from conventionally fractionated radiotherapy, which produces significantly higher nPSAs than stereotactic body radiotherapy (SBRT). We investigated whether an alternative nPSA-based threshold could be used to define post-SBRT BCFs.

MATERIALS AND METHODS

PSA kinetics data on 2038 patients from 9 institutions were retrospectively analyzed for low- and intermediate-risk PCa patients treated with SBRT without ADT. We evaluated the performance of various nPSA-based definitions. We also investigated the relationship of relative PSA decline (rPSA, PSA_18month/PSA_6month) and timing of reaching nPSA + 2 with BCF.

RESULTS

Median follow-up was 71.9 months. BCF occurred in 6.9% of patients. Median nPSA was 0.16 ng/mL. False positivity of nPSA + 2 was 30.2%, compared to 40.9%, 57.8%, and 71.0% for nPSA + 1.5, nPSA + 1.0, and nPSA + 0.5, respectively. Among patients with BCF, the median lead time gained from an earlier nPSA + threshold definition over the Phoenix definition was minimal. Patients with BCF had significantly lower rates of early PSA decline (mean rPSA 1.19 vs. 0.39, p < 0.0001) and were significantly more likely to reach nPSA + 2 ≥ 18 months (83.3% vs. 21.1%, p < 0.0001). The proposed criterion (rPSA ≥ 2.6 or nPSA + 2 ≥ 18 months) had a sensitivity and specificity of 92.4% and 81.5%, respectively, for predicting BCF in patients meeting the Phoenix definition and decreased its false positivity to 6.4%.

CONCLUSION

The Phoenix definition remains an excellent definition for BCF post-SBRT. Its high false positivity can be mitigated by applying additional criteria (rPSA ≥ 2.6 or time to nPSA + 2 ≥ 18 months).

Dose-response with stereotactic body radiotherapy for prostate cancer: A multi-institutional analysis of prostate-specific antigen kinetics and biochemical control

BACKGROUND AND PURPOSE

The optimal dose for prostate stereotactic body radiotherapy (SBRT) is still unknown. This study evaluated the dose-response relationships for prostate-specific antigen (PSA) decay and biochemical recurrence (BCR) among 4 SBRT dose regimens.

MATERIALS AND METHODS

In 1908 men with low-risk (50.0%), favorable intermediate-risk (30.9%), and unfavorable intermediate-risk (19.1%) prostate cancer treated with prostate SBRT across 8 institutions from 2003 to 2018, we examined 4 regimens (35 Gy/5 fractions [35/5, n = 265, 13.4%], 36.25 Gy/5 fractions [36.25/5, n = 711, 37.3%], 40 Gy/5 fractions [40/5, n = 684, 35.8%], and 38 Gy/4 fractions [38/4, n = 257, 13.5%]). Between dose groups, we compared PSA decay slope, nadir PSA (nPSA), achievement of nPSA ≤0.2 and ≤0.5 ng/mL, and BCR-free survival (BCRFS).

RESULTS

Median follow-up was 72.3 months. Median nPSA was 0.01 ng/mL for 38/4, and 0.17-0.20 ng/mL for 5-fraction regimens (p < 0.0001). The 38/4 cohort demonstrated the steepest PSA decay slope and greater odds of nPSA ≤0.2 ng/mL (both p < 0.0001 vs. all other regimens). BCR occurred in 6.25%, 6.75%, 3.95%, and 8.95% of men treated with 35/5, 36.25/5, 40/5, and 38/4, respectively (p = 0.12), with the highest BCRFS after 40/5 (vs. 35/5 hazard ratio [HR] 0.49, p = 0.026; vs. 36.25/5 HR 0.42, p = 0.0005; vs. 38/4 HR 0.55, p = 0.037) including the entirety of follow-up, but not for 5-year BCRFS (≥93% for all regimens, p ≥ 0.21).

CONCLUSION

Dose-escalation was associated with greater prostate ablation and PSA decay. Dose-escalation to 40/5, but not beyond, was associated with improved BCRFS. Biochemical control remains excellent, and prospective studies will provide clarity on the benefit of dose-escalation.

Modelling the effect of race surface and racehorse limb parameters on in silico fetlock motion and propensity for injury

BACKGROUND

The metacarpophalangeal joint (fetlock) is the most commonly affected site of racehorse injury, with multiple observed pathologies consistent with extreme fetlock dorsiflexion. Race surface mechanics affect musculoskeletal structure loading and injury risk because surface forces applied to the hoof affect limb motions. Race surface mechanics are a function of controllable factors. Thus, race surface design has the potential to reduce the incidence of musculoskeletal injury through modulation of limb motions. However, the relationship between race surface mechanics and racehorse limb motions is unknown.

OBJECTIVE

To determine the effect of changing race surface and racehorse limb model parameters on distal limb motions.

STUDY DESIGN

Sensitivity analysis of in silico fetlock motion to changes in race surface and racehorse limb parameters using a validated, integrated racehorse and race surface computational model.

METHODS

Fetlock motions were determined during gallop stance from simulations on virtual surfaces with differing average vertical stiffness, upper layer (e.g. cushion) depth and linear stiffness, horizontal friction, tendon and ligament mechanics, as well as fetlock position at heel strike.

RESULTS

Upper layer depth produced the greatest change in fetlock motion, with lesser depths yielding greater fetlock dorsiflexion. Lesser fetlock changes were observed for changes in lower layer (e.g. base or pad) mechanics (nonlinear), as well as palmar ligament and tendon stiffness. Horizontal friction and fetlock position contributed less than 1° change in fetlock motion.

MAIN LIMITATIONS

Simulated fetlock motions are specific to one horse's anatomy reflected in the computational model. Anatomical differences among horses may affect the magnitude of limb flexion, but will likely have similar limb motion responses to varied surface mechanics.

CONCLUSIONS

Race surface parameters affected by maintenance produced greater changes in fetlock motion than other parameters studied. Simulations can provide evidence to inform race surface design and management to reduce the incidence of injury.

Chaos emerging in soil failure patterns observed during tillage: Normalized deterministic nonlinear prediction (NDNP) and its application

Real-world processes are often combinations of deterministic and stochastic processes. Soil failure observed during farm tillage is one example of this phenomenon. In this paper, we investigated the nonlinear features of soil failure patterns in a farm tillage process. We demonstrate emerging determinism in soil failure patterns from stochastic processes under specific soil conditions. We normalized the deterministic nonlinear prediction considering autocorrelation and propose it as a robust way of extracting a nonlinear dynamical system from noise contaminated motion. Soil is a typical granular material. The results obtained here are expected to be applicable to granular materials in general. From a global scale to nano scale, the granular material is featured in seismology, geotechnology, soil mechanics, and particle technology. The results and discussions presented here are applicable in these wide research areas. The proposed method and our findings are useful with respect to the application of nonlinear dynamics to investigate complex motions generated from granular materials.

Hitting the ground running: Evaluating an integrated racehorse limb and race surface computational model

Race surface mechanics contribute to musculoskeletal injury in racehorses. These mechanics affect ground reaction forces applied to the hoof, and thus limb motions during stance that can contribute to musculoskeletal pathologies. Race surface design has been largely empirical within the industry, with little uniform consensus for injury prevention and performance. Furthermore, race surface installations are too expensive to install experimentally. The objective of this research was to develop and evaluate an integrated racehorse limb and race surface computational model. Combined forward/inverse dynamic simulations of distal leading forelimb motions of a galloping horse during stance were compared to 2D distal leading forelimb kinematics of actual galloping racehorses on race surfaces with measured mechanics. Model predicted angular and translational kinematic profiles had similar qualitative shapes as experimental data, with comparable peak magnitudes. Model predictions of peak metacarpophalangeal position and timing were within 11° and 8ms of mean experimental data. The model overestimated peak fetlock angular velocity on consolidated surfaces (up to 1390°/s), and hoof displacements (up to 4cm) during stance. The model's ability to produce comparable qualitative kinematic profiles to experimental data and biologically reasonable fetlock and hoof motions support the future use of this model to explore the effect of race surface parameters on increasing or decreasing distal limb motions and provide supportive evidence for potential mechanisms of injury.

Modeling equine race surface vertical mechanical behaviors in a musculoskeletal modeling environment

Race surfaces have been associated with the incidence of racehorse musculoskeletal injury, the leading cause of racehorse attrition. Optimal race surface mechanical behaviors that minimize injury risk are unknown. Computational models are an economical method to determine optimal mechanical behaviors. Previously developed equine musculoskeletal models utilized ground reaction floor models designed to simulate a stiff, smooth floor appropriate for a human gait laboratory. Our objective was to develop a computational race surface model (two force-displacement functions, one linear and one nonlinear) that reproduced experimental race surface mechanical behaviors for incorporation in equine musculoskeletal models. Soil impact tests were simulated in a musculoskeletal modeling environment and compared to experimental force and displacement data collected during initial and repeat impacts at two racetracks with differing race surfaces - (i) dirt and (ii) synthetic. Best-fit model coefficients (7 total) were compared between surface types and initial and repeat impacts using a mixed model ANCOVA. Model simulation results closely matched empirical force, displacement and velocity data (Mean R(2)=0.930-0.997). Many model coefficients were statistically different between surface types and impacts. Principal component analysis of model coefficients showed systematic differences based on surface type and impact. In the future, the race surface model may be used in conjunction with previously developed the equine musculoskeletal models to understand the effects of race surface mechanical behaviors on limb dynamics, and determine race surface mechanical behaviors that reduce the incidence of racehorse musculoskeletal injury through modulation of limb dynamics.

A model of Agrobacterium tumefaciens vacuum infiltration into harvested leaf tissue and subsequent in planta transgene transient expression

Agrobacterium-mediated gene transfer, or agroinfiltration, can be a highly efficient method for transforming and inducing transient transgene expression in plant tissue. The technique uses the innate DNA secretion pathway of Agrobacterium tumefaciens to vector a particular plasmid-encoded segment of DNA from the bacteria to plant cells. Vacuum is often applied to plant tissue submerged in a suspension of A. tumefaciens to improve agroinfiltration. However, the effects of vacuum application on agroinfiltration and in planta transient transgene expression have not been well quantified. Here we show that vacuum application and release act to drive A. tumefaciens suspension into the interior of leaf tissue. Moreover, the amount of suspension that enters leaves can be predicted based on the vacuum intensity and duration. Furthermore, we show that transient expression levels of an agroinfiltrated reporter gene vary in response to the amount of A. tumefaciens vacuum infiltrated into leaf tissue, suggesting that vacuum infiltration conditions can be tailored to achieve optimal transient transgene expression levels after agroinfiltration.

Biochemical and molecular markers in renal cell carcinoma: an update and future prospects

Cancer is a big problem in the developed world as well as in developing countries. Renal cell carcinoma (RCC) accounts for approximately 3% of adult malignancies and 90-95% of neoplasms arising from the kidney. RCC is more common in men than in women (2:1), and it most often occurs in patients between the ages of 50-70 years. In all cancers the cancerous cells release particular kind of proteins (called tumour markers) and blood tests are used to detect the presence of these markers. These tumour markers nowadays are an area of interest for oncologists who search for a possible solution in the detection and treatment of RCC. Different kinds of biochemical and molecular markers such as ferritin, MN/CA9, apoptotic index, p53, IL-2, gamma-enolase, CD44, CD95, chromosome instability and loss of heterozygosity have been tested in RCC, but so far no marker fulfils one or the other criteria to be considered as an ideal marker for RCC. This review gives basic and updated information about the different kinds of biomarkers studied in RCC and about the role implementation of genomics and proteomics in RCC.