Evaluation of an online tool about the expected course of disease for glioblastoma patients - A qualitative study

BACKGROUND: Patients with glioblastoma have a short life-expectancy, with median survival rates of 9 to 12 months. Providing information about the expected course of the disease can be complicated. Therefore, an online tool has been developed. The objective of this tool is to better inform patients and proxies, and decrease their uncertainties and improve their quality of life. This study aims to gather experiences of an initial cohort of patient-proxy dyads, to identify if the tool meets the previously mentioned objectives. METHODS: This is a qualitative study based on thematic analysis. Interviews were conducted with 15 patient-proxy dyads. For these interviews, a combined method of think-aloud sessions and semi-structured interviews were used. Audiotapes of these interviews were transcribed verbatim and thematically analyzed. RESULTS: The analysis revealed four major themes, namely, unmet information needs, improvement possibilities, effects of the tool and clinical implementation. Participants indicated that this tool could decrease uncertainties and increase their perceived quality of life. Also, they often mentioned that it could have a positive effect on the efficiency and quality of consultations. CONCLUSION: Participants considered this tool to be useful and effective in decreasing uncertainties for both patients with glioblastoma and their proxies. Moreover, participants brought up that this tool could positively influence the efficiency and quality of consultations. This could lead to more patient participation and empowerment, and could therefore enhance shared decision making and timely advanced care planning

Switching Principal Component Analysis for Modeling Means and Covariance Changes Over Time

Many psychological theories predict that cognitions, affect, action tendencies, and other variables change across time in mean level as well as in covariance structure. Often such changes are rather abrupt, because they are caused by sudden events. To capture such changes, one may repeatedly measure the variables under study for a single individual and examine whether the resulting multivariate time series contains a number of phases with different means and covariance structures. The latter task is challenging, however. First, in many cases, it is unknown how many phases there are and when new phases start. Second, often a rather large number of variables is involved, complicating the interpretation of the covariance pattern within each phase. To take up this challenge, we present switching principal component analysis (PCA). Switching PCA detects phases of consecutive observations or time points (in single subject data) with similar means and/or covariation structures, and performs a PCA per phase to yield insight into its covariance structure. An algorithm for fitting switching PCA solutions as well as a model selection procedure are presented and evaluated in a simulation study. Finally, we analyze empirical data on cardiorespiratory recordings

Respiratory modulation of intensity ratings and psychomotor response times to acoustic startle stimuli

Respiratory interoception may play an important role in the perception of respiratory symptoms in pulmonary diseases. As the respiratory cycle affects startle eye blink responses, startle modulation may be used to assess visceral-afferent signals from the respiratory system. To ascertain the potential impact of brainstem-relayed signals on cortical processes, we investigated whether this pre-attentive respiratory modulation of startle (RMS) effect is also reflected in the modulation of higher cognitive, evaluative processing of the startle stimulus. Twenty-nine healthy volunteers received 80 acoustic startle stimuli (100 or 105 dB(A); 50 ms), which were presented at end and mid inspiration and expiration, while performing a paced breathing task (0.25 Hz). Participants first responded to the startle probes by 'as fast as possible' button pushes and then rated the perceived intensity of the stimuli. Psychomotor response time was divided into 'reaction time' (RT; from stimulus onset to home button release; represents stimulus evaluation) and 'movement time' time (MT; from home button release to target button press). Intensity judgements were higher and RTs accelerated during mid expiration. No effect of respiratory cycle phase was found on eye blink responses and MTs. We conclude that respiratory cycle phase affects higher cognitive, attentional processing of startle stimuli

Frozen section analysis of sentinel lymph nodes in patients with breast cancer does not impair the probability to detect lymph node metastases

Intra-operative frozen section analysis (FS analysis) of sentinel lymph nodes (SLNs) in patients with breast cancer can prevent a second operation for axillary lymph node dissection. In contrast, loss of tissue during FS analysis may impair the probability to detect lymph node metastases. To determine the effect of tissue loss on the probability of detection of metastases, dimensions and tissue loss resulting from intra-operative frozen section analysis were measured for 21 SLNs. In a mathematical model, the influence of tissue loss on the probability to detect metastases was calculated in relation to SLN size for various pathology protocols: an American, a widely used European, the extensive ‘Milan’ and the Dutch protocol. For median-sized SLN 11 × 8 × 5 mm (length × width × height), FS analysis led to a median loss of 680 μm (13.6%) of the height of the SLN. Irrespective of SLN size or used pathology protocol, the probability of detecting 2 mm metastases remained unchanged or even increased (0–12.8%). Moreover, the probability to detect 0.2 mm metastases increased for the majority of tested combinations of SLN size, tissue loss and used protocol. Only when combining maximum tissue loss and smallest SLN size in the Dutch protocol, or when applying the extensive Milan protocol on a median-sized SLN, the probability to detect 0.2 mm metastases decreased by 2.7% and 14.3%, respectively. Contrary to ‘common knowledge’, doing FS analysis of SLNs does not impair the probability to detect lymph node metastases

Intraductal cisplatin treatment in a BRCA-associated breast cancer mouse model attenuates tumor development but leads to systemic tumors in aged female mice

BRCA deficiency predisposes to the development of invasive breast cancer. In BRCA mutation carriers this risk can increase up to 80%. Currently, bilateral prophylactic mastectomy and prophylactic bilateral salpingo-oophorectomy are the only preventive, albeit radical invasive strategies to prevent breast cancer in BRCA mutation carriers. An alternative non-invasive way to prevent BRCA1-associated breast cancer may be local prophylactic treatment via the nipple. Using a non-invasive intraductal (ID) preclinical intervention strategy, we explored the use of combined cisplatin and poly (ADP)-ribose polymerase 1 (PARP1) inhibition to prevent the development of hereditary breast cancer. We show that ID cisplatin and PARP-inhibition can successfully ablate mammary epithelial cells, and this approach attenuated tumor onset in a mouse model of Brca1-associated breast cancer from 153 to 239 days. Long-term carcinogenicity studies in 150 syngeneic wild-type mice demonstrated that tumor incidence was increased in the ID treated mammary glands by 6.3% due to systemic exposure to cisplatin. Although this was only evident in aged mice (median age = 649 days), we conclude that ID cisplatin treatment only presents a safe and feasible local prevention option if systemic exposure to the chemotherapy used can be avoided

Third International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions)

The heterogeneous group of B3 lesions in the breast harbors lesions with different malignant potential and progression risk. As several studies about B3 lesions have been published since the last Consensus in 2018, the 3rd International Consensus Conference discussed the six most relevant B3 lesions (atypical ductal hyperplasia (ADH), flat epithelial atypia (FEA), classical lobular neoplasia (LN), radial scar (RS), papillary lesions (PL) without atypia, and phyllodes tumors (PT)) and made recommendations for diagnostic and therapeutic approaches. Following a presentation of current data of each B3 lesion, the international and interdisciplinary panel of 33 specialists and key opinion leaders voted on the recommendations for further management after core-needle biopsy (CNB) and vacuum-assisted biopsy (VAB). In case of B3 lesion diagnosis on CNB, OE was recommended in ADH and PT, whereas in the other B3 lesions, vacuum-assisted excision was considered an equivalent alternative to OE. In ADH, most panelists (76%) recommended an open excision (OE) after diagnosis on VAB, whereas observation after a complete VAB-removal on imaging was accepted by 34%. In LN, the majority of the panel (90%) preferred observation following complete VAB-removal. Results were similar in RS (82%), PL (100%), and FEA (100%). In benign PT, a slim majority (55%) also recommended an observation after a complete VAB-removal. VAB with subsequent active surveillance can replace an open surgical intervention for most B3 lesions (RS, FEA, PL, PT, and LN). Compared to previous recommendations, there is an increasing trend to a de-escalating strategy in classical LN. Due to the higher risk of upgrade into malignancy, OE remains the preferred approach after the diagnosis of ADH

Third International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions)

The heterogeneous group of B3 lesions in the breast harbors lesions with different malignant potential and progression risk. As several studies about B3 lesions have been published since the last Consensus in 2018, the 3rd International Consensus Conference discussed the six most relevant B3 lesions (atypical ductal hyperplasia (ADH), flat epithelial atypia (FEA), classical lobular neoplasia (LN), radial scar (RS), papillary lesions (PL) without atypia, and phyllodes tumors (PT)) and made recommendations for diagnostic and therapeutic approaches. Following a presentation of current data of each B3 lesion, the international and interdisciplinary panel of 33 specialists and key opinion leaders voted on the recommendations for further management after core-needle biopsy (CNB) and vacuum-assisted biopsy (VAB). In case of B3 lesion diagnosis on CNB, OE was recommended in ADH and PT, whereas in the other B3 lesions, vacuum-assisted excision was considered an equivalent alternative to OE. In ADH, most panelists (76%) recommended an open excision (OE) after diagnosis on VAB, whereas observation after a complete VAB-removal on imaging was accepted by 34%. In LN, the majority of the panel (90%) preferred observation following complete VAB-removal. Results were similar in RS (82%), PL (100%), and FEA (100%). In benign PT, a slim majority (55%) also recommended an observation after a complete VAB-removal. VAB with subsequent active surveillance can replace an open surgical intervention for most B3 lesions (RS, FEA, PL, PT, and LN). Compared to previous recommendations, there is an increasing trend to a de-escalating strategy in classical LN. Due to the higher risk of upgrade into malignancy, OE remains the preferred approach after the diagnosis of ADH

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer

Learning to Detect Triggers of Airway Symptoms: The Role of Illness Beliefs, Conceptual Categories and Actual Experience with Allergic Symptoms

Background: In asthma and allergic rhinitis, beliefs about what triggers allergic reactions often do not match objective allergy tests. This may be due to insensitivity for expectancy violations as a result of holding trigger beliefs based on conceptual relationships among triggers. In this laboratory experiment, we aimed to investigate how pre-existing beliefs and conceptual relationships among triggers interact with actual experience when learning differential symptom expectations.Methods: Healthy participants (N = 48) received information that allergic reactions were a result of specific sensitivities versus general allergic vulnerability. Next, they performed a trigger learning task using a differential conditioning paradigm: brief inhalation of CO2 enriched air was used to induce symptoms, while participants were led to believe that the symptoms came about as a result of inhaled allergens (conditioned stimuli, CS’s; CS+ followed by symptoms, CS- not followed by symptoms). CS+ and CS- stimuli either shared (e.g., birds-mammals) or did not share (e.g. birds-fungi) category membership. During Acquisition, participants reported symptom expectancy and symptom intensity for all triggers. During a Test 1 day later, participants rated symptom expectancies for old CS+/CS- triggers, for novel triggers within categories, and for exemplars of novel trigger categories. Data were analyzed using multilevel models.Findings: Only a subgroup of participants (n = 22) showed differences between CO2 and room air symptoms. In this group of responders, analysis of symptom expectancies during acquisition did not result in significant differential symptom CS+/CS- acquisition. A retention test 1 day later showed differential CS+/CS- symptom expectancies: When CS categories did not share category membership, specific sensitivity beliefs improved retention of CS+/CS- differentiation. However, when CS categories shared category membership, general vulnerability beliefs improved retention of CS+/CS- differentiation. Furthermore, participants showed some selectivity in generalization of symptom expectancies to novel categories, as symptom expectancies did not generalize to novel categories that were unrelated to CS+ or CS- categories. Generalization to novel categories was not affected by information about general vulnerability or specific sensitivities.Discussion: Pre-existing vulnerability beliefs and conceptual relationships between trigger categories influence differential symptom expectancies to allergic triggers