Browsing by Subject "GRADING SYSTEM"

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  • Aho, Tommi; Mustonen, Laura; Kalso, Eija; Harno, Hanna (2020)
    Background Douleur Neuropathique 4 (DN4) is a screening questionnaire to help identify neuropathic pain (NP) in clinical practice and research. We tested the accuracy of the DN4 questionnaire in stratifying possible NP (pNP) and definite NP (dNP) in patients operated for breast cancer. Methods We studied 163 patients from a longitudinal cohort of breast cancer operated patients 4-9 years after surgery. pNP or dNP were classified according to the NP grading system. Surgeon-verified intercostobrachial nerve resection was used as a confirmatory test for dNP. A receiver-operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated to test the diagnostic accuracy (sensitivity, specificity, positive and negative predictive values) of the DN4. Additionally, we studied clinical factors that associated with a positive screening outcome in the interview part of the DN4 (DN4i). Results DN4i and DN4 showed significant accuracy in stratifying patients with pNP or dNP with cut-off scores 3 and 4 resulting to sensitivity of 66.2% and 79.4% and specificity of 77.8% and 92.6%, respectively. pNP and dNP patients showed differences in sensory descriptors of pain according to DN4i items. Screening positive on DN4i associated with dNP and younger age. Conclusions Full DN4 could stratify pNP and dNP patients in a chronic postsurgical NP patient group operated for breast cancer. Additionally, DN4i showed significant accuracy in stratifying pNP and dNP, but an examination is necessary to obtain proper accuracy. Demographic factors may have an impact on the screening outcome of DN4i. Significance DN4 stratifies possible and definite postsurgical peripheral neuropathic pain. DN4i may also show this, but full DN4 is more accurate. We confirm DN4i as a valid screening tool for NP.
  • Ollila, Hely; Paajanen, Juuso; Wolff, Henrik; Ilonen, Ilkka; Sutinen, Eva; Välimäki, Katja; Östman, Arne; Anttila, Sisko; Kettunen, Eeva; Räsänen, Jari; Kallioniemi, Olli; Myllärniemi, Marjukka; Mäyränpää, Mikko I.; Pellinen, Teijo (2021)
    Malignant pleural mesothelioma (MPM) has a rich stromal component containing mesenchymal fibroblasts. However, the properties and interplay of MPM tumor cells and their surrounding stromal fibroblasts are poorly characterized. Our objective was to spatially profile known mesenchymal markers in both tumor cells and associated fibroblasts and correlate their expression with patient survival. The primary study cohort consisted of 74 MPM patients, including 16 patients who survived at least 60 months. We analyzed location-specific tissue expression of seven fibroblast markers in clinical samples using multiplexed fluorescence immunohistochemistry (mfIHC) and digital image analysis. Effect on survival was assessed using Cox regression analyses. The outcome measurement was all-cause mortality. Univariate analysis revealed that high expression of secreted protein acidic and cysteine rich (SPARC) and fibroblast activation protein in stromal cells was associated with shorter survival. Importantly, high expression of platelet-derived growth factor receptor beta (PDGFRB) in tumor cells, but not in stromal cells, was associated with shorter survival (hazard ratio [HR] = 1.02, p <0.001). A multivariable survival analysis adjusted for clinical parameters and stromal mfIHC markers revealed that tumor cell PDGFRB and stromal SPARC remained independently associated with survival (HR = 1.01, 95% confidence interval [CI] = 1.00-1.03 and HR = 1.05, 95% CI = 1.00-1.11, respectively). The prognostic effect of PDGFRB was validated with an artificial intelligence-based analysis method and further externally validated in another cohort of 117 MPM patients. In external validation, high tumor cell PDGFRB expression associated with shorter survival, especially in the epithelioid subtype. Our findings suggest PDGFRB and SPARC as potential markers for risk stratification and as targets for therapy.
  • Paajanen, Juuso; Laaksonen, Sanna; Kettunen, Eeva; Ilonen, Ilkka; Vehmas, Tapio; Salo, Jarmo; Räsänen, Jari; Sutinen, Eva; Ollila, Hely; Mäyränpää, Mikko I.; Myllärniemi, Marjukka; Wolff, Henrik (2020)
    Diffuse malignant mesothelioma (DMM) of the pleura is a rare and aggressive disease, where the long-term survival (LTS) rate is low. The epithelioid subtype is the most prevalent form of DMM with the best prognosis. In order to study prognostic histopathologic factors associated with extended survival in epithelioid DMM, we examined 43 tumors from patients with survival over five years (long-term survivals [LTS]) and compared the findings with 84 tumors from a reference group with average survival (RG). We analyzed the tumors considering previously published histopathological prognostic features and attempted to identify additional morphological features predictive of extended survival. Most of the LTS tumors presented with nuclear grade I (n = 34,90%) and a tubulopapillary growth pattern (n = 30,70%). One LTS tumor had necrosis. In contrast, nuclear grade II (n = 49,61%) and solid growth pattern (n = 59,70%) were more frequent in RG, and necrosis was present in 16 (19%) tumors. We also evaluated the association of asbestos lung tissue fiber burden quantified from autopsy samples with histopathological features and found that elevated asbestos fiber was associated with higher nuclear grade (p <0.001) and the presence of necrosis (p = 0.021). In univariate survival analysis, we identified the following three novel morphological features associated with survival: exophytic polypoid growth pattern, tumor density, and single mesothelium layered tubular structures. After adjustments, low nuclear grade (p <0.001) and presence of exophytic polypoid growth (p = 0.024) were associated with prolonged survival. These results may aid in estimating DMM prognosis.
  • Baron, Ralf; Maier, Christoph; Attal, Nadine; Binder, Andreas; Bouhassira, Didier; Cruccu, Giorgio; Finnerup, Nanna B.; Haanpää, Maija; Hansson, Per; Huellemann, Philipp; Jensen, Troels S.; Freynhagen, Rainer; Kennedy, Jeffrey D.; Magerl, Walter; Mainka, Tina; Reimer, Maren; Rice, Andrew S. C.; Segerdahl, Marta; Serra, Jordi; Sindrup, Soren; Sommer, Claudia; Toelle, Thomas; Vollert, Jan; Treede, Rolf-Detlef; German Neuropathic Pain Res Networ; EUROPAIN; NEUROPAIN Consortia (2017)
    Patients with neuropathic pain are heterogeneous in etiology, pathophysiology, and clinical appearance. They exhibit a variety of painrelated sensory symptoms and signs (sensory profile). Different sensory profiles might indicate different classes of neurobiological mechanisms, and hence subgroups with different sensory profilesmight respond differently to treatment. The aim of the investigation was to identify subgroups in a large sample of patients with neuropathic pain using hypothesis-free statistical methods on the database of 3 large multinational research networks (German Research Network on Neuropathic Pain (DFNS), IMI-Europain, and Neuropain). Standardized quantitative sensory testing was used in 902 (test cohort) and 233 (validation cohort) patients with peripheral neuropathic pain of different etiologies. For subgrouping, we performed a cluster analysis using 13 quantitative sensory testing parameters. Three distinct subgroupswith characteristic sensory profileswere identified and replicated. Cluster 1 (sensory loss, 42%) showed a loss of small and large fiber function in combination with paradoxical heat sensations. Cluster 2 (thermal hyperalgesia, 33%) was characterized by preserved sensory functions in combination with heat and cold hyperalgesia and mild dynamic mechanical allodynia. Cluster 3 (mechanical hyperalgesia, 24%) was characterized by a loss of small fiber function in combinationwith pinprick hyperalgesia and dynamic mechanical allodynia. All clusters occurred across etiologies but frequencies differed. We present a new approach of subgrouping patients with peripheral neuropathic pain of different etiologies according to intrinsic sensory profiles. These 3 profiles may be related to pathophysiological mechanisms and may be useful in clinical trial design to enrich the study population for treatment responders.
  • Vollert, Jan; Maier, Christoph; Attal, Nadine; Bennett, David L. H.; Bouhassira, Didier; Enax-Krumova, Elena K.; Finnerup, Nanna B.; Freynhagen, Rainer; Gierthmuehlen, Janne; Haanpaa, Maija; Hansson, Per; Hullemann, Philipp; Jensen, Troels S.; Magerl, Walter; Ramirez, Juan D.; Rice, Andrew S. C.; Schuh-Hofer, Sigrid; Segerdahl, Marta; Serra, Jordi; Shillo, Pallai R.; Sindrup, Soeren; Tesfaye, Solomon; Themistocleous, Andreas C.; Toelle, Thomas R.; Treede, Rolf-Detlef; Baron, Ralf j (2017)
    In a recent cluster analysis, it has been shown that patients with peripheral neuropathic pain can be grouped into 3 sensory phenotypes based on quantitative sensory testing profiles, which are mainly characterized by either sensory loss, intact sensory function and mild thermal hyperalgesia and/or allodynia, or loss of thermal detection and mild mechanical hyperalgesia and/or allodynia. Here, we present an algorithm for allocation of individual patients to these subgroups. The algorithm is nondeterministic-ie, a patient can be sorted to more than one phenotype-and can separate patients with neuropathic pain from healthy subjects (sensitivity: 78%, specificity: 94%). We evaluated the frequency of each phenotype in a population of patients with painful diabetic polyneuropathy (n = 151), painful peripheral nerve injury (n = 335), and postherpetic neuralgia (n = 97) and propose sample sizes of study populations that need to be screened to reach a subpopulation large enough to conduct a phenotype-stratified study. The most common phenotype in diabetic polyneuropathy was sensory loss (83%), followed by mechanical hyperalgesia (75%) and thermal hyperalgesia (34%, note that percentages are overlapping and not additive). In peripheral nerve injury, frequencies were 37%, 59%, and 50%, and in postherpetic neuralgia, frequencies were 31%, 63%, and 46%. For parallel study design, either the estimated effect size of the treatment needs to be high (> 0.7) or only phenotypes that are frequent in the clinical entity under study can realistically be performed. For crossover design, populations under 200 patients screened are sufficient for all phenotypes and clinical entities with a minimum estimated treatment effect size of 0.5.