| 1. |
- Haese, Alexander, et al.
(författare)
-
Human glandular kallikrein 2 levels in serum for discrimination of pathologically organ-confined from locally-advanced prostate cancer in total PSA-levels below 10 ng/ml
- 2001
-
Ingår i: The Prostate. - : Wiley. - 0270-4137 .- 1097-0045. ; 49:2, s. 101-109
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: We measured serum levels of human glandular kallikrein 2 (hK2) in patients treated with radical retropubic prostatectomy (rrP) for clinically localized prostate cancer (PCa) with a total PSA (tPSA)-level below 10 ng/ml to investigate whether hK2 can be applied to preoperatively distinguish organ-confined (pT2a/b) from nonorgan-confined (> or = pT3a)-PCa more accurately than total PSA. Further, we evaluated hK2, free- and tPSA-concentrations in all pathologic stages of PCa. METHODS: 161 serum samples from men scheduled for rrP were collected 1 day before surgery prior to any prostatic manipulation. Pathologic work-up revealed > or = pT3a-PCa in 48 and pT2a/b-PCa in 113 patients. HK2-levels in serum were measured using an immunofluorometric assay with an analytical sensitivity of 0.5 pg/ml, a functional sensitivity of 5 pg/ml and insignificant cross-reactivity with PSA (< 0.005%). Total (tPSA) and free PSA (fPSA) levels were measured using a commercially available assay from which we calculated %fPSA and an algorithm that combined hK2 and PSA-levels [hK2] x [tPSA/fPSA]. Means, medians, and ranges were calculated for pT2a/b vs. >/= pT3a-PCa and for all pathologic stages. Statistical significance of differences was calculated using Mann-Whitney-U and Kruskal-Wallis tests. Calculation of receiver-operator-characteristic (ROC) curves were performed for hK2, [hK2] x [tPSA/fPSA] and tPSA to compare diagnostic performance. RESULTS: A mean tPSA level in serum of 6.12 ng/ml in > or = pT3a-PCa was not significantly different (P = 0.366) from 5.78 ng/ml in pT2a/b-PCa. Also, there were no statistically significantly different levels of fPSA (P = 0.947) or %fPSA (0.292) for these two groups. By contrast, mean hK2-level in pT2a/b-PCa of 80 pg/ml was significantly different (P = 0.004) from a mean hK2 level of 120 pg/ml in > or = pT3a-PCa as shown by Mann-Whitney-analysis Moreover, the algorithm of [hK2] x [tPSA/fPSA] was significantly lower (P = 0.0004) in pT2a/b-PCa vs. > or = pT3a-PCa. Calculation of areas under curve (AUC) by receiver-operator-characteristics (ROC) demonstrated that the AUC for hK2 (0.64) was larger and the AUC for [hK2] x [tPSA/fPSA] (=0.68) significantly larger (P = 0.007) compared to the AUC of tPSA (0.55). Furthermore, Kruskal-Wallis Test revealed a highly significant correlation to pathologic stage using hK2 (P = 0.008) and [hK2] x [tPSA/fPSA] (P = 0.0015) compared to no significant differences in serum concentration of tPSA (P = 0.296). Also at tPSA-levels from 10-20 ng/ml, the hK2-levels in pT2a/b-PCa were close to significantly different (P = 0.051) from those in men with >/= pT3a-PCa, while the algorithm of [hK2] x [tPSA/fPSA] in that tPSA-range was significantly lower (P = 0.002) in pT2a/b-PCa compared to > or = pT3a0-PCa. CONCLUSIONS: Highly significant differences in serum concentration enable hK2 to be a powerful predictor of organ-confined disease and pathologic stage of clinically localized prostate cancer, especially in the PSA-range below 10 ng/ml. As such, there are important clinical consequences for the application of hK2 for the adequate treatment of prostate cancer patients, i.e., the option of nerve-sparing surgery.
|
|
| 2. |
- Pettersson, Ola, 1972-
(författare)
-
Model-free execution monitoring in behavior-based mobile robotics
- 2004
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In the near future, autonomous mobile robots are expected to assist us by performing service tasks in many different areas, including transportation, cleaning, mining, or agriculture. In order to manage these tasks in a changing and partially unpredictable environment, without the help of humans, the robot must have the ability to plan its actions and to execute them robustly and in a safe way. Since the real world is dynamic and not fully predictable, the robot must also have the ability to detect when the execution does not proceed as planned, and to correctly identify the causes of the failure. An execution monitoring system is a system that allows the robot to detect and classify these failures. Most current approaches to execution monitoring in robotics are based on the idea of predicting the outcomes of the robot's actions by using some sort of model, and comparing the predicted outcomes with the observed ones. In contrary, this thesis explores the use of model-free approaches to execution monitoring, that is, approaches that do not use predictive models. These approaches solely observe the actual execution of the robot, and detect certain patterns that indicate a problem. In this thesis, we show that pattern recognition techniques can be applied to realize model-free execution monitoring by classifying observed behavioral patterns into normal or faulty behaviors. We investigate the use of several such techniques, and verify their utility in a number of experiments involving the navigation of a mobile robot in indoor environments. Statistical measures are used to compare the results given from several realistic simulations. Our approach has also been successfully tested on a real robot navigating in an office environment. Interesting, this test has shown that we can train a model-free execution monitor in simulation, and then use it in a real robot.
|
|
