Synchronization and supportive interventions: an interpersonal physiology study of the terapeutic micro-process from the point of view of the expressive-supportive continuum.

openQuesto elaborato intende approfondire la sincronizzazione fisiologica tra paziente e terapeuta in un’ottica micro-processuale. Le premesse teoriche si basano sull’approccio embodied che ha permesso il superamento del dualismo mente-corpo. Il presente studio ha analizzato due psicoterapie brevi della durata di 16 sedute ciascuna. I partecipanti sono un terapeuta di orientamento dinamico e due giovani pazienti (Francesco e Clara). La sincronizzazione fisiologica tra paziente e terapeuta è stata analizzata attraverso la misurazione della conduttanza cutanea. Inoltre, la sincronizzazione fisiologica è stata indagata in relazione all’outcome psicoterapeutico e in corrispondenza di varie tipologie di intervento proposte dal terapeuta. Gli interventi sono stati codificati lavorando sui trascritti delle sedute attraverso il Psychodynamic Intervention Rating Scale (PIRS; Cooper & Bond, 1992). L’outcome dei due pazienti è stato valutato tramite il Clinical Outcomes in Routine Evaluation Outcome Measure (CORE-OM; Evans et al., 2000) e sulla base dei trascritti dell’ultima seduta del trattamento. La terapia di Clara presenta un outcome positivo, mentre quella di Francesco un outcome non positivo. I risultati ottenuti evidenziano che per Clara sono gli interventi espressivi quelli maggiormente associati a un alto livello di sincronizzazione fisiologica tra paziente e terapeuta. In particolare, gli interventi classificati come reflections (R) e clarification (CL) mostrano livelli elevati di sincronizzazione. Considerando il PIRS iper-dettagliato e declinato attraverso il continuum espressivo-supportivo di Gabbard (2018) è la codifica CL2 delle clarification (CL) a determinare la significatività dell’intera categoria. Al contrario, per Francesco gli interventi con maggiore sincronizzazione filologica sono quelli supportivi, più nello specifico gli interventi codificati dal PIRS come support strategies (SS). Considerando il PIRS iper-dettagliato e declinato attraverso il continuum espressivo-supportivo di Gabbard (2018) è la codifica SS2 delle support strategies (SS) a determinare la significatività dell’intera categoria. In aggiunta a ciò, nella psicoterapia di Clara si evidenza una maggiore frequenza di interventi espressivi, mentre in quella di Francesco una più elevata presenza di interventi supportivi. Infine, per entrambi i pazienti, si osserva una maggiore frequenza dalla metà della terapia degli interventi interpretativi e una loro decrescita al termine del trattamento

TAMs PD-L1(+) in the reprogramming of germ cell tumors of the testis

Background: In recent years, several studies focused on the process of reprogramming of seminoma (S) cells, which regulates the transition from pure S (P-S) to S component (S-C) of mixed germ cell tumors of the testis (GCTT) and finally to embryonal carcinoma (EC) and other nonseminomatous GCTT (NS-GCTT). The accepted pathogenetic model is driven and regulated by cells (macrophages, B- and T-lymphocytes) and molecules of the tumor microenvironment (TME). Herein, we tested a series of GCTT with double staining (DS) for CD68-PD-L1 to evaluate tumor-associated macrophages (TAMs) expressing programmed death-ligand 1 (PD-L1) [TAMs PD-L1(+)] and clarify if these cells may be involved in establishing the fate of GCTT. Methods: We collected 45 GCTT (comprising a total of 62 different components of GCTT). TAMs PD-L1(+) were evaluated with three different scoring systems [TAMs PD-L1(+)/mm2, TAMs PD-L1(+)/mm2H-score, TAMs PD-L1(+) %], and compared using pertinent statistic tests (Student's t-test and Mann-Whitney U test). Results: We found that TAMs PD-L1(+) values were higher in S rather than EC (p = 0.001, p = 0.015, p = 0.022) and NS-GCTT (p < 0.001). P-S showed statistically significant differences in TAMs PD-L1(+) values compared to S-C (p < 0.001, p = 0.006, p = 0.015), but there were no differences between S-C and EC (p = 0.107, p = 0.408, p = 0.800). Finally, we found statistically significant differences also in TAMs PD-L1(+) values between EC and other NS-GCTT (p < 0.001). Conclusions: TAMs PD-L1(+) levels gradually decrease during the reprogramming of S cells {P-S [(high values of TAMs PD-L1(+)] → S-C and EC [(intermediate values of TAMs PD-L1(+)] → other NS-GCTT [(low values of TAMs PD-L1(+)], supporting a complex pathogenetic model where the interactions between tumor cells and TME components [and specifically TAMs PD-L1(+)] play a key role in determining the fate of GCTT

Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential

Background: Prognosis of oral squamous cell carcinoma (OSCC) is difficult to exactly assess on pre-operative biopsies. Since OSCC DNA methylation profile has proved to be a useful pre-operative diagnostic tool, the aim of the present study was to evaluate the prognostic impact of DNA methylation profile to discriminate OSCC with high and low aggressive potential. Methods: 36 OSCC cases underwent neoplastic cells collection by gentle brushing of the lesion, before performing a pre-operative biopsy. The CpG islands methylation status of 13 gene (ZAP70, ITGA4, KIF1A, PARP15, EPHX3, NTM, LRRTM1, FLI1, MiR193, LINC00599, MiR296, TERT, GP1BB) was studied by bisulfite Next Generation Sequencing (NGS). A Cox proportional hazards model via likelihood-based component-wise boosting was used to evaluate the prognostic power of the CpG sites. Results: The boosting estimation identified five CpGs with prognostic significance: EPHX3-24, EPHX3-26, ITGA4-3, ITGA4-4, and MiR193-3. The combination of significant CpGs provided promising results for adverse events prediction (Brier score = 0.080, C-index = 0.802 and AUC = 0.850). ITGA4 had a strong prognostic power in patients with early OSCC. Conclusions: These data confirm that the study of methylation profile provides new insights into the molecular mechanisms of OSCC and can allow a better OSCC prognostic stratification even before surgery

Breakthrough Cancer Pain: Preliminary Data of The Italian Oncologic Pain Multisetting Multicentric Survey (IOPS-MS)

Introduction: An ongoing national multicenter survey [Italian Oncologic Pain multiSetting Multicentric Survey (IOPS-MS)] is evaluating the characteristics of breakthrough cancer pain (BTP) in different clinical settings. Preliminary data from the first 1500 cancer patients with BTP enrolled in this study are presented here. Methods: Thirty-two clinical centers are involved in the survey. A diagnosis of BTP was performed by a standard algorithm. Epidemiological data, Karnofsky index, stage of disease, presence and sites of metastases, ongoing oncologic treatment, and characteristics of background pain and BTP and their treatments were recorded. Background pain and BTP intensity were measured. Patients were also questioned about BTP predictability, BTP onset (≤10 or >10 min), BTP duration, background and BTP medications and their doses, time to meaningful pain relief after BTP medication, and satisfaction with BTP medication. The occurrence of adverse reactions was also assessed, as well as mucosal toxicity. Results: Background pain was well controlled with opioid treatment (numerical rating scale 3.0 ± 1.1). Patients reported 2.5 ± 1.6 BTP episodes/day with a mean intensity of 7.5 ± 1.4 and duration of 43 ± 40 min; 977 patients (65.1%) reported non-predictable BTP, and 1076 patients (71.7%) reported a rapid onset of BTP (≤10 min). Higher patient satisfaction was reported by patients treated with fast onset opioids. Conclusions: These preliminary data underline that the standard algorithm used is a valid tool for a proper diagnosis of BTP in cancer patients. Moreover, rapid relief of pain is crucial for patients’ satisfaction. The final IOPS-MS data are necessary to understand relationships between BTP characteristics and other clinical variables in oncologic patients. Funding: Molteni Farmaceutici, Italy

Factors influencing the clinical presentation of breakthrough pain in cancer patients

Background: The aim of this study was to identify potential variables influencing the clinical presentation of breakthrough cancer pain (BTP). Methods: Cancer patients with a diagnosis of BTP were enrolled. Demographic and clinical characteristics, as well as background pain and BTP characteristics were collected. Multivariate analyses were conducted to assess the correlation between BTP characteristics and the variables examined. Results: Data of 4016 patients were analysed. Average daily number of BTP episodes was 2.4, mean intensity was 7.5, and a mean duration was 43.3 min. A short onset BTP was observed in 68.9% of patients. In 30.5% of patients BTP was predictable. There were 86.0% of participants who reported a marked interference of BTP with their daily activities. Furthermore, 86.8% of patients were receiving opioids for the management of BTP. The average time to meaningful pain relief was 16.5 min and 70.9% of patients were satisfied with their BTP medications. Age, head and neck cancer, Karnofsky, background pain intensity, predictable and fast onset BTP were independently associated with the number of BTP episodes. BTP pain intensity was independently associated with background pain intensity, fast onset BTP, and Karnofsky. Neuropathic pain mechanism was independently associated with unpredictable BTP. Variables independently associated with a longer duration of BTP were age, place of visit, cancer diagnosis, disease-oriented therapy, background pain intensity and mechanism, and unpredictable BTP. Age, Karnofsky, background pain intensity, fast onset, and long duration of BTP were independently associated with interference with daily activity. Conclusions: BTP has a variable presentation depending on interdependent relationships among its different characteristics

Factors Influencing the Clinical Presentation of Breakthrough Pain in Cancer Patients

Background: The aim of this study was to identify potential variables influencing the clinical presentation of breakthrough cancer pain (BTP). Methods: Cancer patients with a diagnosis of BTP were enrolled. Demographic and clinical characteristics, as well as background pain and BTP characteristics were collected. Multivariate analyses were conducted to assess the correlation between BTP characteristics and the variables examined. Results: Data of 4016 patients were analysed. Average daily number of BTP episodes was 2.4, mean intensity was 7.5, and a mean duration was 43.3 min. A short onset BTP was observed in 68.9% of patients. In 30.5% of patients BTP was predictable. There were 86.0% of participants who reported a marked interference of BTP with their daily activities. Furthermore, 86.8% of patients were receiving opioids for the management of BTP. The average time to meaningful pain relief was 16.5 min and 70.9% of patients were satisfied with their BTP medications. Age, head and neck cancer, Karnofsky, background pain intensity, predictable and fast onset BTP were independently associated with the number of BTP episodes. BTP pain intensity was independently associated with background pain intensity, fast onset BTP, and Karnofsky. Neuropathic pain mechanism was independently associated with unpredictable BTP. Variables independently associated with a longer duration of BTP were age, place of visit, cancer diagnosis, disease-oriented therapy, background pain intensity and mechanism, and unpredictable BTP. Age, Karnofsky, background pain intensity, fast onset, and long duration of BTP were independently associated with interference with daily activity. Conclusions: BTP has a variable presentation depending on interdependent relationships among its different characteristics

Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study

PURPOSE A large proportion of patients with cancer suffer from breakthrough cancer pain (BTcP). Several unmet clinical needs concerning BTcP treatment, such as optimal opioid dosages, are being investigated. In this analysis the hypothesis, we explore with an unsupervised learning algorithm whether distinct subtypes of BTcP exist and whether they can provide new insights into clinical practice. METHODS Partitioning around a k-medoids algorithm on a large data set of patients with BTcP, previously collected by the Italian Oncologic Pain Survey group, was used to identify possible subgroups of BTcP. Resulting clusters were analyzed in terms of BTcP therapy satisfaction, clinical features, and use of basal pain and rapidonset opioids. Opioid dosages were converted to a unique scale and the BTcP opioids-to-basal pain opioids ratio was calculated for each patient. We used polynomial logistic regression to catch nonlinear relationships between therapy satisfaction and opioid use. RESULTS Our algorithm identified 12 distinct BTcP clusters. Optimal BTcP opioids-to-basal pain opioids ratios differed across the clusters, ranging from 15% to 50%. The majority of clusters were linked to a peculiar association of certain drugs with therapy satisfaction or dissatisfaction. A free online tool was created for new patients’ cluster computation to validate these clusters in future studies and provide handy indications for personalized BTcP therapy. CONCLUSION This work proposes a classification for BTcP and identifies subgroups of patients with unique efficacy of different pain medications. This work supports the theory that the optimal dose of BTcP opioids depends on the dose of basal opioids and identifies novel values that are possibly useful for future trials. These results will allow us to target BTcP therapy on the basis of patient characteristics and to define a precision medicine strategy also for supportive care

Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study

PURPOSE A large proportion of patients with cancer suffer from breakthrough cancer pain (BTcP). Several unmet clinical needs concerning BTcP treatment, such as optimal opioid dosages, are being investigated. In this analysis the hypothesis, we explore with an unsupervised learning algorithm whether distinct subtypes of BTcP exist and whether they can provide new insights into clinical practice. METHODS Partitioning around a k-medoids algorithm on a large data set of patients with BTcP, previously collected by the Italian Oncologic Pain Survey group, was used to identify possible subgroups of BTcP. Resulting clusters were analyzed in terms of BTcP therapy satisfaction, clinical features, and use of basal pain and rapidonset opioids. Opioid dosages were converted to a unique scale and the BTcP opioids-to-basal pain opioids ratio was calculated for each patient. We used polynomial logistic regression to catch nonlinear relationships between therapy satisfaction and opioid use. RESULTS Our algorithm identified 12 distinct BTcP clusters. Optimal BTcP opioids-to-basal pain opioids ratios differed across the clusters, ranging from 15% to 50%. The majority of clusters were linked to a peculiar association of certain drugs with therapy satisfaction or dissatisfaction. A free online tool was created for new patients' cluster computation to validate these clusters in future studies and provide handy indications for personalized BTcP therapy. CONCLUSION This work proposes a classification for BTcP and identifies subgroups of patients with unique efficacy of different pain medications. This work supports the theory that the optimal dose of BTcP opioids depends on the dose of basal opioids and identifies novel values that are possibly useful for future trials. These results will allow us to target BTcP therapy on the basis of patient characteristics and to define a precision medicine strategy also for supportive care

Factors influencing the clinical presentation of breakthrough pain in cancer patients

Background: The aim of this study was to identify potential variables influencing the clinical presentation of breakthrough cancer pain (BTP). Methods: Cancer patients with a diagnosis of BTP were enrolled. Demographic and clinical characteristics, as well as background pain and BTP characteristics were collected. Multivariate analyses were conducted to assess the correlation between BTP characteristics and the variables examined. Results: Data of 4016 patients were analysed. Average daily number of BTP episodes was 2.4, mean intensity was 7.5, and a mean duration was 43.3 min. A short onset BTP was observed in 68.9% of patients. In 30.5% of patients BTP was predictable. There were 86.0% of participants who reported a marked interference of BTP with their daily activities. Furthermore, 86.8% of patients were receiving opioids for the management of BTP. The average time to meaningful pain relief was 16.5 min and 70.9% of patients were satisfied with their BTP medications. Age, head and neck cancer, Karnofsky, background pain intensity, predictable and fast onset BTP were independently associated with the number of BTP episodes. BTP pain intensity was independently associated with background pain intensity, fast onset BTP, and Karnofsky. Neuropathic pain mechanism was independently associated with unpredictable BTP. Variables independently associated with a longer duration of BTP were age, place of visit, cancer diagnosis, disease-oriented therapy, background pain intensity and mechanism, and unpredictable BTP. Age, Karnofsky, background pain intensity, fast onset, and long duration of BTP were independently associated with interference with daily activity. Conclusions: BTP has a variable presentation depending on interdependent relationships among its different characteristics