Objectives: Neuropsychological tests are an important basis for the memory impairment diagnosis in Alzheimer’s disease (AD). However, multiple memory tests might be conflicting within-subjects and lead to uncertain diagnoses in some cases. This study proposed a framework to diagnose the uncertain cases of memory impairment.Methods: We collected 2,386 samples including AD, mild cognitive impairment (MCI), and cognitive normal (CN) using 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and three different neuropsychological tests  from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A deep learning (DL) framework using FDG-PET was proposed to diagnose uncertain memory impairment cases that were conflicting between tests. Subsequent ANOVA, chi-squared, and t-test were used to explain the potential causes of uncertain cases.Results: For certain cases in the testing set, the proposed DL framework outperformed other methods with 95.65% accuracy. For the uncertain cases, its positive diagnoses had a significant (p < 0.001) worse decline in memory function than negative diagnoses in a longitudinal study of 40 months on average. In the memory-impaired group, uncertain cases were mainly explained by an AD metabolism pattern but mild in extent (p < 0.05). In the healthy group, uncertain cases were mainly explained by a non-energetic mental state (p < 0.001) measured using a global deterioration scale (GDS), with a significant depression-related metabolism pattern detected (p < 0.05).Conclusion: A DL framework for diagnosing uncertain cases of memory impairment is proposed. Proved by longitudinal tracing of its diagnoses, it showed clinical validity and had application potential. Its valid diagnoses also provided evidence and explanation of uncertain cases based on the neurodegeneration and depression mental state. Neuropsychological tests, such as Mini-Mental State Examination (MMSE) , AlzheimMoreover, the cause of these uncertain cases remains unclear. Major explanations include the lack of sensitivity of these tests , especiaInspired by these works, to explore a diagnosing method and an explanation with evidence for the uncertain cases in memory impairment related to AD, we tried to diagnose the uncertain cases using a designed deep learning (DL) framework on 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) using a large set of samples, verify its validity using longitudinal memory function progress, and figure out neurological evidence and cause using groupwise statistical analyses.In the field of computer-aided diagnosis (CAD), more researchers are focusing on analyzing neuroimages using the DL algorithm . It abstHowever, most CAD researches dealt with certain labeled samples  before tInspired by these studies, we proposed a semi-supervised learning framework based on 3D CNN  that ext1 which is the largest ongoing project for the analysis of AD, covering all subphases of ADNI project from September 2006 to October 2019 . All available FDG-PET and corresponding MRI images up to April 2020 were collected to ensure a large data amount. One case of data included FDG-PET/CT scanning for glucose metabolism, T1-weighted magnetization prepared rapid gradient-echo (MPRAGE) MRI, memory assessment in three major neuropsychological tests, namely, MMSE, ADAS-Cog, and CDR, and global deterioration scale ,Three major neuropsychological tests including MMSE, ADAS-Cog, and CDR were carried out within 6 months and the images were collected for each FDG-PET scan. We did not choose other popular tests, such as the Montreal Cognitive Assessment (MoCA), because these were less applied in ADNI set. These neuropsychological tests are comprehensive evaluations of different cognitive functions, and memory is the most significant and primary one. The delayed word recall test is applied in the same way both in MMSE and ADAS-Cog. To make different tests more comparable, this study concentrated on the delayed word recall tests of MMSE  and ADAS-Cog , and CDR score of memory (CDR-Memory). In detail, MMSE-Recall was scored 0–3 based on how many words of 3 were recalled, ADAS-Cog-Recall was scored 0–30 based on how many words of 30 were recalled, and CDR-Memory was scored 0, 0.5, 1, 2, and 3 as healthy, suspected, mild, moderate, and severe memory impairment.Each FDG-PET image was grouped based on whether the memory cognitive impairment was certainly impaired or healthy in the three neuropsychological tests. First, if MMSE-Recall ≤ 1, ADAS-Cog-Recall < 12 (defined by “mean − standard deviation”), and CDR-Memory ≥ 1, the case will be grouped into “certain impaired.” In reverse, if MMSE-Recall > 1, ADAS-Cog-Recall > 23 (defined by “mean + standard deviation”), and CDR-Memory = 0, the case will be grouped into “certain healthy.” The rest of the cases that the three tests are conflicting with each other will be grouped as “uncertain cases” and diagnosed using the DL framework proposed in this study. The whole grouping is shown in via the routine of unified segmentation algorithm  was divided by mean uptake of the whole pons  in a certain group were evaluated using fivefold cross-validation. Then, all FDG-PET images in the uncertain group were placed into the trained DL framework, which was diagnosed to be memory-impaired/healthy. The whole flowchart is shown in After grouping certain and uncertain cases, the corresponding FDG-PET images were used to diagnose uncertain cases using the DL framework. First, for evaluating the classification performance of each method, all images  model was used to classify impaired/healthy from the FDG-PET image of each case. The structure of the model is shown in 6)  , linear Second, to evaluate the accuracy of the DL framework’s diagnoses on uncertain cases, we used the memory testing scores in the progress of the longitudinal study of each subject, with 40 months on average. Because the longitudinal progress of memory impairment is a key concern of AD and also a reliable marker indicating whether true impaired or healthy state at baseline, a nice diagnosis framework should tell apart the subjects between memory impairment in progress and healthy memory function, using baseline FDG-PET as inputs.t-distributed stochastic neighbor embedding (t-SNE)  and  (t-SNE) , were apTime complexity evaluation was performed for each method. The DL algorithms were evaluated using a special metric named floating-point operations per second (FLOP) because the big “O” is not suitable for too many free variables in the DL networks. Other traditional methods were evaluated using the big “O” notation.t-test was applied between both voxel-wise and region of interests (ROI)-wise SUVr, and the multiple comparison correction was applied by family-wise error (FWE) or false discovery rate (FDR) depending on the extent of significance, with cluster extent > 5. The age, gender, education level, and ApoE gene types were taken into account as covariates because they could reasonably influence the neurodegeneration in FDG-PET. The t-test was also applied to test scores between groups.The p-value to ensure a credible significance.Two-way ANOVA was applied to judge whether the variance of total GDS scores was significantly contributed by certain/uncertain, impaired/healthy, and the interaction between these two factors. Because of the different sample sizes between groups, groups will be randomly sampled to equal the smallest size 294 by applying two-way ANOVA. Considering the randomness of sampling, we repeated the random sampling and applied ANOVA 100 times, and recorded the mean P-values in GDS were strictly corrected by FWE because 15 tests and a total score were tested and listed.The chi-squared test was applied to judge the significant ratio difference between groups, such as gender, ApoE, and each single GDS test with binary value in comparisons. Linear regression was applied to evaluate the longitudinal tendency of neuropsychological test scores, using months after baseline as an independent variable and scores as a dependent variable. The 95% CI of the fitted result was shown.7.All statistical tests were performed using the statistics and machine learning toolbox in MATLAB R2019In total, 2,386 samples were obtained from 1,247 subjects and tested using FDG-PET and neuropsychological tests. These samples included 332 subjects with AD, 1,347 subjects with MCI, and 707 subjects with CN. According to the grouping criteria of memory test performance, 312 subjects were grouped as “certain impaired” cases, 333 subjects were grouped as “certain healthy” cases, and 1,741 subjects were grouped as uncertain cases. All demographic information can be found in Nine different models were trained on the FDG-PET images of certain cases with fivefold cross-validation. After evaluating the binary classification performance, the DL framework has an obvious comprehensive advantage over other models, separately in accuracy (95.90%), precision (97.01%), sensitivity (93.59%), F1 score (95.27%), and AUC (98.15%) . The timTo judge whether the diagnoses classified using the DL framework in the uncertain cases are reliable, we chose to track the longitudinal memory function progress of each uncertain case and regarded it as an evaluation criterion for the diagnoses with the baseline FDG-PET.The total longitudinal cases are 8,870 for ADAS-Cog-Recall, 8,865 for MMSE-Recall, 9,323 for CDR-Memory, and the cases that three tests completed at the same time are 6,912. The longitudinal time lengths are 40.38 ± 29.32 months for MMSE-Recall, 40.91 ± 29.68 months for ADAS-Cog-Recall, and 42.07 ± 30.40 months for CDR-Memory.After the DL framework had diagnosed these uncertain cases, as for the longitudinal changes , impairet-test results are shown in t-test map view in slices is found in Owing to the DL diagnoses for uncertain cases, we could then manage to analyze the glucose metabolism state between four groups based on the labels, namely, certain/uncertain and impaired/healthy. The However, in the second row of t-SNE unsupervised topological representation of high-dimensional features extracted using the DL framework is shown in The P-value was corrected using FWE, resulting in p < 0.0031 for significance. As a result, only the GDS-Energy test was not significantly (p = 0.4329) correlated to the impaired/healthy memory impairment of subjects, but significantly (p < 0.001) correlated to the certain/uncertain state of subjects (p < 0.001), both in baseline and longitudinal studies  unstable neuropsychological test results longitudinally than energetic subjects, including all three tests (p < 0.001) representing the self-assessment of memory capacity had both significant effects between impaired/healthy and certain/uncertain cases.To explore the latent relationships and interactions between mental state and uncertain cases, the chi-squared test for every single question of GDS and two-way ANOVA was applied on the total GDS score, with two factors  evaluated. subjects , which m studies . Moreoveee tests . Additiot-tests between energetic and non-energetic cases, respectively, on the four diagnosing groups, and the t-test map view in slices is found in p < 0.05; FDR-corrected), and the glucose metabolism of energetic subjects are stronger in the binary anterior middle cingulate, the wide range of frontal lobe, and a small region of the temporoparietal lobe, while weaker in binary cerebellum regions 8 and 9, which is partly similar to the significant difference between uncertain group and certain healthy group presented in The influence of the energetic state was also evaluated using the glucose metabolism of FDG-PET. We applied As the results of neuropsychological tests might be conflicting within the same subject and lead to an uncertain case and diagnosis, we proposed a 3D-CNN-DL framework to diagnose memory impairment in uncertain cases using FDG-PET images, and the corresponding longitudinal study was proved to be clinically valid between positive and negative diagnoses. Then, by analyzing the FDG-PET and GDS between groups, we figured out that a mild-extent AD-related neurodegeneration state is a potential cause for an impaired sample to be uncertain, and a non-energetic mental state with a depression-related metabolism pattern is a potential cause for a healthy sample to be uncertain.Neuropsychological tests, such as MMSE, ADAS-Cog, and CDR, are convenient and effective methods for screening and diagnosing dementia. These tests contain several questions for multiple cognitive aspects, including memory, orientation, attention, and language. Among these, memory impairment is the most common and vulnerable cognitive aspect during neurodegenerative diseases such as MCI  and AD , so we fa priori knowledge like the definition of ROI. To the best of our knowledge, most of these studies focused on training and applying the DL frameworks both on labeled cases (positive or negative pre-diagnosed by experts), and neglected to exploit the capability of diagnosing uncertain and difficult cases even for experts. So, we tried to use the FDG-PET images to diagnose uncertain memory impairment. To give an evaluation criterion for these diagnosing results, we studied all the available longitudinal progress (40 months on average) of 2,386 cases up to April 2020 in the ADNI dataset, which are more than 6,912 cases in the longitudinal study, then we found that the impaired diagnoses using the DL framework were significantly worse in longitudinal memory function decline than the healthy diagnoses using the DL framework. Especially in the CDR-Memory progress per month, the increasing slope of uncertain healthy cases was as flat as certain healthy cases, while the uncertain impaired cases showed around four times the increasing speed of healthy cases. This significant evidence proved that the DL framework could manage to tell apart the impaired and healthy impairment in uncertain cases and had clinical validity and application potential. Its clinical potential can be concluded as a more accurate diagnosis when facing conflicting neuropsychological test results and ensure less occurrence of misdiagnosis. Subsequently, its diagnosis for uncertain cases can reduce the potentially inappropriate medication and plan a more valid treatment in time, which is valuable for AD and MCI subjects.Because of these disadvantages of neuropsychological tests, using the DL algorithm on neuroimages to diagnose neurodegenerative diseases is getting popular recently, especially in classifying AD dementia . The capUntil present, the causes of conflict test conclusion and uncertain cases remain unclear. Major viewpoints blamed it on the different sensitivity or different design of tests . Howevert-test between groups with strict significance threshold and the t-SNE of feature in DL showed that the glucose metabolism intensity is decreasing progressively by this order of groups: certain healthy, uncertain healthy, uncertain impaired, and certain impaired. This evidence proves that the uncertain cases have a detectable neuropathological basis and shows an intermediate state between impaired and healthy cases. In other words, the neurodegenerative progress of an uncertain group is a state between healthy and diseased. The hypometabolism regions between certain and uncertain impaired cases are the typically affected regions of AD: frontal lobe, temporoparietal lobe, limbic systems such as the hippocampus and subcutaneous nuclei, which implies that the neurodegenerative extent of this group is not enough to reach a certain diagnosis but has the same impaired pattern.For AD-related causes, the FDG-PET p < 0.001) in uncertain cases than certain cases but not different (p = 0.4329) between impaired and healthy cases. This means a non-energetic mental state is a key factor that can lead to uncertain cases regardless of the state of memory impairment. The baseline (t-tests between energetic and non-energetic subjects in the four groups (For depression-related causes, we collected the GDS scores of each sample in the baseline, which contained 15 questions for different types of depression mental state. The chi-squared test showed two valuable results. First, the GDS-energy is significantly different (baseline  and longbaseline  between baseline . Correspr groups  are onlyr groups  of mild r groups .To conclude the relationship between the two causes, first, they are not independent or exclusive, but both exist and interact with each other by neurological basis such as neurodegeneration. Second, the priority of them varies when the subjects are healthy or impaired, while a mild-extent AD-related neurodegenerative progress is potentially the major cause of uncertain impaired cases, and non-energetic depression-related mental state is potentially the major cause of uncertain healthy cases, which could guide clinical practice to deal with uncertain cases reasonably and effectively. Third, the evidence of neurodegeneration and mental causes can verify each other, as proposed above.Our study had several limitations. First, because we obtained samples from ADNI as a large multisite dataset and collected all available data to keep a large sample amount, the multisite effect of PET scanning and several unbalanced demographical information cannot be avoided, but we strictly used them as covariates in statistical tests. Second, although using MRI for PET preprocessing, because the scanning time interval between PET and MRI varies, we only chose FDG-PET as an evaluation of neurodegenerative progress, which might miss information that other modalities provided. Third, because of the priority of memory impairment in AD, we only focused on this aspect among many cognitive aspects, other aspects such as orientation and language or even total score are also valuable to be analyzed later.We proposed the DL framework based on FDG-PET for diagnosing uncertain cases of memory impairment related to AD, which was clinically reliable for diagnosing uncertain cases and proved valid in the corresponding longitudinal study. As for the cause and evidence of uncertain cases, for uncertain memory-impaired subjects, the uncertainty is mainly explained by mild-extent AD-related neurodegeneration. For uncertain memory-healthy subjects, the uncertainty is mainly explained by a non-energetic mental state and depression-related metabolism pattern.http://adni.loni.usc.edu/. Please note that access is contingent on adherence to the ADNI Data Use Agreement and the publications’ policies.Publicly available datasets were analyzed in this study. This data can be found here: WZ: methodology, software, validation, formal analysis, writing–original draft, writing–review and editing, and data curation. TZ: resources. TP: visualization. SZ: investigation. BN and HL: conceptualization and supervision. BS: supervision and project administration. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Multiplexed imaging is a recently developed and powerful single-cell biology research tool. However, it presents new sources of technical noise that are distinct from other types of single-cell data, necessitating new practices for single-cell multiplexed imaging processing and analysis, particularly regarding cell-type identification. Here we created single-cell multiplexed imaging datasets by performing CODEX on four sections of the human colon  using a panel of 47 oligonucleotide-barcoded antibodies. After cell segmentation, we implemented five different normalization techniques crossed with four unsupervised clustering algorithms, resulting in 20 unique cell-type annotations for the same dataset. We generated two standard annotations: hand-gated cell types and cell types produced by over-clustering with spatial verification. We then compared these annotations at four levels of cell-type granularity. First, increasing cell-type granularity led to decreased labeling accuracy; therefore, subtle phenotype annotations should be avoided at the clustering step. Second, accuracy in cell-type identification varied more with normalization choice than with clustering algorithm. Third, unsupervised clustering better accounted for segmentation noise during cell-type annotation than hand-gating. Fourth, Z-score normalization was generally effective in mitigating the effects of noise from single-cell multiplexed imaging. Variation in cell-type identification will lead to significant differential spatial results such as cellular neighborhood analysis; consequently, we also make recommendations for accurately assigning cell-type labels to CODEX multiplexed imaging. SetWe compared single-cell quantified data without processing to that processed using four different normalization techniques:Each marker intensity was Z normalized separately for all cells within the dataset. This normalized the range of each marker as fluorescent intensities of each marker can depend on antibody staining strength and exposure times.The first Z normalization was performed on each marker intensity, and then another Z normalization was applied to each cell. These values were then transformed into probabilities. Finally, a negative log transformation was applied to the complement of the probabilities. Because the first Z normalization equalizes signal intensities, marker Z scores can be compared. Furthermore, as each cell should only be positive for between one and five markers of the 47 recognized by antibodies in the staining panel, applying the second Z normalization identifies positive markers with high probability. Using a negative log transformation of the complement of the probability is necessary to amplify values of high probabilities for input into clustering algorithms.st and 99th percentiles were found to cap minimum and maximum values, respectively, for each fluorescent channel and then each value in the channel was normalized by taking the difference between minimum over the range of values. Reducing to the 99th percentile aids removes artificially high background fluorescent intensities often seen in imaging datasets.First the 1An arcsinh transformation was performed on marker intensities, and the resulting values were scaled with a cofactor of 150. This type of normalization is appropriate when dataset contain low or negative values resulting from background subtraction.https://cellengine.com/). X-shift with angular distance, X-shift with Euclidian distance, and k-means clustering were performed using the VorteX software available from our GitHub site (https://github.com/nolanlab/vortex). Default settings were used with k values obtained from the elbow-point inflection from each clustering technique. Leiden-based clustering was performed using the scanpy Python package with default parameters.Hand gating was carried out using a hierarchical strategy to label each cell as shown in F-score analysis was performed as described in We conducted our analysis on data we collected as a part of the Human BioMolecular Atlas Program (HuBMAP) consortia effort that focuses on systematic mapping healthy tissue structure across human organ systems and making the data publicly available . For thi).The antibody panel includes targets for discriminating several major epithelial subtypes of the colon, stromal cell types, and both adaptive and innate immune cell types ; level 2, 20 cell types; level 3, 14 cell types; and level 4, 7 cell types , min-max, or arcsinh, or left in its original raw format  at higher levels of granularity  were not (average F-score of 0.05), regardless of normalization technique or clustering algorithm used.Understanding the inter-cell variation of F-scores can help us gauge the appropriate granularity for cell-type assignment. Certain cell types  were consistently categorized accurately (average F-score of 0.6), whereas other cell types   there was high intra-cell variation of F-scores (~0.7 range), whereas for other cell types  there was considerably less intra-cell variation of F-scores (~0.15 range). We highlight three examples with both high and low intra-cell variation are instructive of the differences in normalization and clustering techniques.Neuroendocrine cells are a rare cell type  and are uniquely positive for chromogranin A (CHGA). CHGA had a low signal intensity in the fluorescence but also had a low background signal  and are identified due to expression of CD45, CD15, and CD16, which are markers also shared by other immune and epithelial cells. CD15 and CD16 had higher background signals than other markers  identified based on cytokeratin staining and lack of specialized epithelial markers . The intra-cell F-score variation was low for these cells. Differences between normalization and clustering technique were less pronounced than for neuroendocrine cells and neutrophils, although for enterocytes agreement depended more on the clustering technique than for rarer cells types. For enterocytes, Leiden and It is important to select the normalization and clustering technique that maximizes the performance on the cell types  that have high intra-cell variation of F-scores. Our analysis indicates that a normalization method such as Z normalization reduces clustering artifacts associated with noise associated with low signal or high background.F-score averages increased at lower levels of granularity as expected, although, surprisingly, the endothelial cell population had a consistent low average score . This strengthens the argument that phenotypic cell-type calling should be limited in initial clustering due to the low confidence of these cell-type definitions  as there were areas where the tissue folded during the cutting process, and some edge effects that were noticeable in the folded area . Smooth muscle cells were often incorrectly assigned as cells of goblet or epithelium origin as demonstrated by assignment to the muscularis externa neighborhood , min-max, or arcsinh), Z normalization was the most consistent technique for handling different sources of noise including low intensity signal, high background signal, segmentation noise, and imaging artifacts. Furthermore, Z normalization resulted in accurate identification of both rare and common cell types. Consequently, we recommend Z normalization of values from each marker prior to cell-type identification  and was confounded by segmentation noise such as bleed through of cytokeratin signal into neighboring endothelial cells.Accuracy in cell-type identification depended more on normalization technique than it did on the downstream unsupervised clustering algorithms. The algorithms tested, which were the graph-based Leiden, the density-based X-shift with either Euclidian or angular distances , and k-m+ T cells vs. inactivated CD4+ T cells) were inaccurately assigned by all normalization and clustering algorithms. Consequently, irrespective of the clustering algorithm used, settings should be chosen to produce significantly higher number of clusters than cell types expected . Also, here we imaged healthy human intestine, whereas in tumor tissues there can be in EMT  and MET transition states. This also makes separation of cell types challenging with EMT or MET markers. However, computational analysis such as pseudotime analysis of the transition continuum would be interesting once broader cell types have been established.With this in mind, selection of antibodies thus plays a significant role in downstream spatial tissue analysis and recognition of cell types. In short, if the research question is to maximize the number of cell types identified to understand the distinct landscape of the tissue, then antibody markers that were restricted to certain cell types (e.g. CHGA-Neuroendocrine) should be selected. On the other hand, phenotypic markers are useful in comparing a certain cell type state in greater detail between experimental conditions.Beyond making a choice between phenotypic and cell-type markers, antibody clone selection can significantly affect staining quality. Improving the signal-to-noise ratio makes it easier to separate out cell types from one another in unsupervised clustering. Best practices for selecting antibodies can be found in a recent primer . BrieflyIn the future, we expect that machine learning-based cell-type annotation transfer models will be built using accurately annotated data . This tyAdditional analytical methods will be needed to address the root causes of additional noise in multiplexed imaging data. As examples, efforts are focused on cell segmentation with generalizable whole-cell segmentation masks trained from a variety of multiplexed imaging data . Second,https://doi.org/10.5061/dryad.dfn2z352c.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: HubMAP, HBM977.PCGP.852, HBM575.THQM.284, HBM462.JKCN.863, HBM334.QWFV.953, HBM938.KMNW.825; Dryad Conceptualization: JH, YG, and GPN. Methodology: JH and YG. Formal Analysis: JH, YT, and YG. Writing: JH, YT, YG, and GPN. Funding acquisition: GPN. All authors contributed to the article and approved the submitted version.This work was supported by the U.S. National Institutes of Health ; the U.S. Department of Defense ; the U.S. Food and Drug Administration ; Cancer Research UK (C27165/A29073); the Bill and Melinda Gates Foundation (OPP1113682); the Cancer Research Institute; the Parker Institute for Cancer Immunotherapy; the Kenneth Rainin Foundation (2018–575); the Silicon Valley Community Foundation (2017-175329 and 2017-177799-5022); the Beckman Center for Molecular and Genetic Medicine; Juno Therapeutics, Inc (122401).; Pfizer, Inc (123214).; Celgene, Inc .; Vaxart, Inc (137364).; and the Rachford & Carlotta A. Harris Endowed Chair to GN. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. JH was supported by an NIH T32 Fellowship (T32CA196585) and an American Cancer Society - Roaring Fork Valley Postdoctoral Fellowship (PF-20-032-01-CSM).GPN received research support from Pfizer, Vaxart, Celgene, and Juno Therapeutics during the course of this work. YG and GPN are inventors on US patent 9909167, granted to Stanford University, that covers some aspects of the technology described in this paper. YG and GPN have equity in and/or are scientific advisory board members of Akoya Biosciences, Inc.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Patients with prostate cancer often experience pain, fatigue and other negative symptoms that can lead to poorer quality of life. Enzalutamide is a prostate cancer therapy that is effective across the disease continuum from early-state cancer patients through to patients with metastatic castration-resistant disease. In this study, we evaluated how enzalutamide impacts patients’ quality of life. We found that patients with early disease maintained low pain levels and symptom-related burden when treated with enzalutamide or with a control treatment, and that patients with advanced disease who received enzalutamide experienced mitigated negative impacts compared to controls. Furthermore, it took longer for patients treated with enzalutamide to report experiencing a reduction in quality of life, and this was most pronounced for patients with advanced cancer. Enzalutamide can be tolerated by patients with early or advanced prostate cancer and delays both disease progression and the associated deterioration of quality of life.p = 0.2998; nmCRPC (confirmed) p = 0.0044; mCRPC (unconfirmed) p < 0.0001). Across the prostate cancer continuum, enzalutamide is well-tolerated and delays the negative impact that disease progression has on quality of life.This review examines the impact of treatment with enzalutamide on health-related quality of life (HRQoL) in prostate cancer patients across the disease continuum based on pivotal clinical trials. We assessed the effect of enzalutamide on pain, symptom burden and overall HRQoL from randomized controlled trials. Patient experience was evaluated in men with metastatic hormone-sensitive prostate cancer (mHSPC), non-metastatic castration-resistant prostate cancer (nmCRPC) and metastatic castration-resistant prostate cancer (mCRPC) (pre-chemotherapy and post-chemotherapy). Patients across the disease continuum reported a generally positive status at baseline, with relatively low levels of pain and impairment due to cancer-related symptoms and high HRQoL. For patients with earlier-state prostate cancer, pain and symptom-related burden were low at study entry and remained so, regardless of whether patients received enzalutamide or control treatment. Patients with more advanced disease reported mitigation in pain and symptom burden while receiving treatment with enzalutamide. Enzalutamide was observed to slow deterioration of overall HRQoL most for patients with nmCRPC or mCRPC   The androgen receptor inhibitor enzalutamide has demonstrated consistent benefits in men with prostate cancer at various stages of the disease, from hormone-sensitive prostate cancer (HSPC) to metastatic (m) and non-metastatic (nm) castration-resistant prostate cancer (CRPC) ,2,3,4,5.In addition to safety and efficacy, measures of health-related quality of life (HRQoL) are increasingly important to patients and providers, and can be used to monitor treatment efficacy and disease progression ,7. HRQoLThis paper examines HRQoL data from four pivotal enzalutamide trials to present key insights into the patients’ HRQoL experience across disease states, ranging from mHSPC through to mCRPC in the post-chemotherapy setting. This review aims to highlight the impact of treatment with enzalutamide for prostate cancer on HRQoL measures that are meaningful to patients across the disease continuum.This is a summary review of the patient-reported outcome (PRO) data from pivotal enzalutamide publications that used additional unpublished data to supplement published material . Detailed methods are provided in The impact of enzalutamide on PRO measures across the disease spectrum, pain, symptom burden and overall HRQoL was assessed. The Functional Assessment of Cancer Therapy—Prostate (FACT-P), EuroQol 5-Dimension 5-Level questionnaire (EQ-5D-5L) and Brief Pain Inventory–Short Form (BPI-SF) were administered in the pivotal enzalutamide trials to evaluate the patient experience. For a detailed description of these measures and an overview of the frequency of administration of the FACT-P, EQ-5D-5L and BPI-SF across studies, refer to The FACT-P  is a selThe EQ-5D-5L  is a staThe BPI-SF  measuresDetails of the statistical analysis used in the clinical trials can be found in corresponding publications ,13,14,15Baseline characteristics of patients included in the different studies are provided in Completion rates for PROs are found in At study entry, patients across the disease continuum reported a generally positive outlook, with relatively low levels of pain, low levels of impairment due to cancer-related symptoms and high overall HRQoL . Across For patients with earlier-state prostate cancer, pain at study entry was low and remained so, while patients with more advanced disease reported a delayed progression of pain when receiving treatment with enzalutamide .Patients in each trial/disease state reported mild-to-moderate levels of pain (mean PCS−Pain scores ranging from 13.2 (nmCRPC) to 9.7 (post-chemotherapy mCRPC) out of a total of 16) at baseline. For all subscales of the FACT-P, including the PCS−Pain subscale, note that higher scores indicate better HRQoL. For patients with earlier disease states  receiving either enzalutamide or control treatment, pain scores remained close to baseline levels ,12. For Analysis of change from baseline indicated statistically significant differences in pain scores between treatment groups, favoring enzalutamide in patients with CRPC . For patFor pre-chemotherapy patients with mCRPC, there was no difference in PCS−Pain scores between treatment groups at the 61-week endpoint , althougTime to pain progression as measured by the PCS−Pain score was significantly delayed in patients with mCRPC treated with enzalutamide (pre-chemotherapy and post-chemotherapy) compared to controls . Regardlp = 0.085) for patients with nmCRPC. Data were not available for patients with post-chemotherapy mCRPC. Data from the BPI-SF supported data from the PCS−Pain subscale: enzalutamide had a positive benefit on time to deterioration in the BPI-SF worst pain scores . There wProstate cancer symptoms were evaluated using the FACT-P PCS. Prostate cancer symptoms appeared to be mitigated in patients with mCRPC receiving enzalutamide, while earlier-state patients receiving enzalutamide were more similar to control patients.As with pain, patients across the studies tended to enter at baseline with relatively low symptom levels: the lowest mean symptom burden (34.7 out of 48) was reported by patients with nmCRPC, while the highest levels were found in patients with post-chemotherapy mCRPC. Results suggest that enzalutamide was most protective against increased symptom burden for patients with more advanced disease.FACT-P PCS scores show that enzalutamide mitigated prostate cancer symptoms in later states of prostate cancer . AdjusteFor those patients with less-advanced disease (mHSPC or nmCRPC), no marked changes from baseline were observed between enzalutamide and controls, and prostate cancer symptom burden appeared relatively stable across the trials, regardless of treatment. The analysis demonstrated that no statistically significant changes from baseline in FACT-P PCS scores were observed at week 73 for patients with mHSPC or at week 97 for patients with nmCRPC in either of the treatment arms, indicating that both groups reported stable outcomes over time ,12.However, for later-state patients with mCRPC, particularly those who had undergone chemotherapy, enzalutamide limited the effects of progression on HRQoL and provided protection from symptoms and effects related to prostate cancer compared to the control treatment. In particular, for those with post-chemotherapy mCRPC, while symptoms improved in the enzalutamide arm, a worsening was observed for the control arm. For patients with mCRPC (pre-chemotherapy and post-chemotherapy), there was a statistically significant difference in PCS change from baseline between treatment groups at all time points. Furthermore, by the trial endpoints (weeks 61 (pre-chemotherapy PREVAIL) and 25 (post-chemotherapy AFFIRM)), the control group had experienced a clinically meaningful worsening, while the enzalutamide group had not . BetweenCompared to the control treatment, enzalutamide significantly delayed time to deterioration in FACT-P PCS scores for patients with nmCRPC and mCRPC, with no impact in hormone-sensitive patients . In patiEnzalutamide significantly delayed time to deterioration of PCS scores vs. control treatment in patients with CRPC, regardless of the metastatic status of the disease, with an increased benefit (lower HR) as the disease progressed towards post-chemotherapy. Time to deterioration for the FACT-P PCS was prolonged by enzalutamide in patients with nmCRPC, as well as for those patients with mCRPC, both in the pre-chemotherapy and post-chemotherapy settings ,13.For overall well-being reported by patients, enzalutamide was observed to slow the deterioration of HRQoL, particularly for those with nmCRPC and mCRPC.HRQoL scores followed similar trends to the previously outlined symptom scores: enzalutamide maintained high baseline HRQoL scores in a similar manner to those receiving androgen deprivation therapy (ADT) plus placebo in patients with earlier disease states , while the protective effect of enzalutamide on HRQoL compared to control treatment was most noticeable in patients with mCRPC in the pre-chemotherapy and post-chemotherapy settings.Change from baseline in FACT-P total score and EQ-5D-5L Visual Analog Scale (VAS) score showed that enzalutamide maintained baseline HRQoL across the disease continuum, including in more advanced prostate cancer . For lesEarly-state patients reported relatively stable HRQoL, regardless of treatment. Although there was an early trend toward between-group differences in patients with nmCRPC, the change from baseline was comparable between groups at 97 weeks .For pre-chemotherapy and post-chemotherapy patients with mCRPC ,15, enzaAcross the disease continuum, there was a trend indicating that enzalutamide delayed time to deterioration of HRQoL as measured by the FACT-P compared to controls . This trThe HR for time to deterioration was consistently <1, i.e., favored enzalutamide over control treatment, regardless of whether the definition included the first confirmed or unconfirmed event. However, the delay in deterioration reached statistical significance only for unconfirmed time to deterioration in patients with CRPC. Patients with mHSPC on enzalutamide had a similar time to deterioration (determined by a 10-point decrease in the FACT-P) as control patients . Time toThe trends observed in the VAS were generally in line with those observed for the FACT-P but are statistically significant, favoring enzalutamide .This study demonstrates that treatment with enzalutamide across the spectrum of prostate cancer, although associated with some AEs ,2,3,4, dTaken together, the results from the FACT-P, EQ-5D-5L and BPI-SF suggest that HRQoL, symptom burden and pain are likely to remain stable in patients with mHSPC and nmCRPC, but gradually deteriorate when patients progress to mCRPC. Treatment with enzalutamide may mitigate disease impacts for these later-state patients. This effect is most evident when examining time to deterioration. Conversely, earlier-state patients receiving enzalutamide experience a similar stability of symptom and function scores compared to control-treated patients. These results are broadly supported by the European Organisation for Research and Treatment of Cancer 25-Item Prostate Cancer questionnaire data in patients with mHSPC and nmCRPC, reported elsewhere ,12.Since patients with mHSPC and nmCRPC had relatively high HRQoL and low pain at study entry, it was difficult to identify significant improvements. In contrast, in patients with mCRPC for whom HRQoL has been shown to rapidly deteriorate in the natural disease course, enzalutamide significantly delays this deterioration over control treatment.These results are in line with findings from a large UK-based population-based study of over 35,000 patients that observed that patients across the disease continuum tend to report similar HRQoL levels . It has This study has several limitations. First, the selection criteria for patients in each of the pivotal trials were not the same across trials, making it more difficult to draw direct comparisons across studies. Additionally, the treatment history in PREVAIL and AFFIRM  may not be aligned with future clinical practice. Furthermore, the time period for each pivotal trial differs as a consequence of the variable disease states .Second, patients with higher ECOG performance status scores were either excluded or, in the case of the AFFIRM trial, represented a minority of the overall patient cohort , which may have led to an overestimation of the HRQoL and an underestimation of pain . Additionally, some trials  remain immature in their follow-up, where further follow-up time is needed to understand the relationship between treatment, progression and PROs.Lastly, the endpoints included in the summary are not fully independent scores. Specifically, the FACT-P PCS includes the FACT-P PCS−Pain score, while the FACT-P total score includes the PCS. Therefore, it is possible that the advantages observed are not as diverse as implied by the terminology reflecting pain, prostate cancer symptoms and HRQoL.This novel approach seeks to pragmatically respond to the needs of clinicians and decision-makers and is the first time, to our knowledge, that the patient experience of a particular prostate cancer therapy has been evaluated across the disease state continuum. Furthermore, the clinical trials in this review included a large international sample size deemed to be representative of patients globally, who, at baseline, reflected the characteristics of typical patients at each disease state. The studies also used the same comparator across trials (standard of care at the time of the study). Lastly, the questionnaires are validated in this population and have been widely used in other studies. Future studies may continue to assess the benefit of enzalutamide across prostate cancer disease states, for instance through post-marketing surveillance trials or registry studies.In addition to efficacy and safety, treatment choices in medicine should consider the impact of the intervention on the quality of life of the patient. Enzalutamide is well-tolerated across the prostate cancer continuum and can reduce the negative impact that disease progression has on HRQoL. This is valuable information for patients, clinicians and other stakeholders involved in treatment management decisions globally.


The long noncoding RNAs (lncRNAs) play the important role in tumor occurrence and progression, and the epithelial to mesenchymal transition (EMT) is the critical process for tumor migration. However, the role of EMT-related lncRNA in hepatocellular carcinoma (HCC) has not been elucidated.  In this study, we selected the EMT-related lncRNAs in HCC by using data from The Cancer Genome Atlas database (TCGA). Two prognostic models of the overall survival (OS) and relapse-free survival (RFS) were constructed and validated through Cox regression model, Kaplan-Meier analysis, and the receiver-operating characteristic (ROC) curves. The unsupervised clustering analysis was utilized to investigate the association between EMT-lncRNAs with tumor immune microenvironment. ESTIMATE algorithm and gene set enrichment analysis (GSEA) were used to estimate tumor microenvironment and associated KEGG pathways.  Two EMT-related lncRNA prognostic models of OS and RFS were constructed. Kaplan-Meier curves showed the dismal prognosis of OS and RFS in the group with high-risk score. The ROC curves and AUC values in two prognostic models indicated the discriminative value in the training set and validation set. Patients with HCC were clustered into two subgroups according the unsupervised clustering analysis. Lnc-CCNY-1 was selected as the key lncRNA. GSVA analysis showed that lnc-CCNY-1 was negatively associated with peroxisome proliferator-activated receptor (PPAR) signaling pathway and positively correlated with CELL cycle pathway.  Two EMT-related lncRNA prognostic models of OS and RFS were constructed to discriminate patients and predict prognosis of HCC. EMT-related lncRNAs may play a role on prognosis of HCC by influencing the immune microenvironment. Lnc-CCNY-1 was selected as the key EMT-related lncRNA for further exploration. Hepatocellular carcinoma (HCC) is the most common cancer and the third leading cause of cancer-related deaths worldwide . DespiteThe epithelial to mesenchymal transition (EMT) is a multistep biological process, which is characterized by epithelial cell lose polarity and connection to the basement membrane and gains the ability of invasion, migration, and resistance to apoptosis. EMT has been reported to play a crucial role in early steps of metastasis in carcinoma progression . SeveralDue to the development of next-generation sequencing technology, the tumor gene characteristics received more attention. LncRNA characterized by greater than 200 nt in length was a form of noncoding RNAs. It was reported that lncRNAs are incorporated in several pathophysiological processes of tumor progression –13. SeveImmunotherapy has made great advances and has been emerged as an effective treatment in HCC and other malignant tumors –20. HoweIn this study, we identified differentially expressed EMT-related lncRNAs by comparing the tumor samples and the normal samples from The Cancer Genome Atlas database (TCGA) database. Then, the prognostic EMT-related lncRNA models were constructed and validated. The key EMT-related lncRNA which was simultaneously related to overall survival (OS) and disease-free survival (RFS) was selected for further investigation. ESTIMATE and CIBERSORT algorithms were performed to explore the intratumoral immune landscape.The gene expression profile of HCC patients was downloaded from TCGA-LIHC database, and the clinical information of these patients was retrieved from cBioportal database. We selected a list of lncRNA by using the gene annotation in the GENCODE project. All data were downloaded from public database, so ethical approval and informed consent were waived.http://dbemt.bioinfo-minzhao.org/download.cgi) was downloaded. We performed Pearson correlation analysis to select EMT-related lncRNAs, when the correlation coefficient ∣r | >0.4 and p < 0.05. We obtained the differentially expressed EMT-related lncRNAs by comparing the tumor samples and the normal samples using the “limma” package in the R software, with ∣logFC | >1 and a false discovery rate < 0.05.The EMT-related gene profile from EMT gene database  curves at 1, 3, and 5 years were utilized to evaluate the predictive ability of this model. To further analyze prognostic value in different stages of HCC patients, we performed the ROC curves at 1, 3, and 5 years in four stages.R | >0.4 and p < 0.005. Cytoscape was utilized to visualize the coexpression network.We performed the Pearson correlation analysis to explore the interaction between mRNA and EMT-related lncRNA. It was considered significant association, with the criterion of correlation coefficient ∣We utilized the unsupervised consensus approach to generate two clusters of HCC cohort through “Consensus Cluster Plus” package, to investigate the association between EMT-lncRNAs with tumor immune microenvironment. ESTIMATE algorithm  was usedBased on the multivariate Cox proportional hazard regression analysis, differentially expressed EMT-related lncRNAs were identified, including for OS signature and for RFS signature. Among them, EMT-related lncRNA lnc-CCNY-1 was both associated with OS and RFS. The Kaplan-Meier survival curves and log-rank test were performed for lncRNAs for further research. The EMT-related lncRNAs which showed the more relevant to prognosis with prognosis of HCC was identified.Gene Set Variation Analysis (GSVA) was utilized to characterize pathways or signature summaries in samples of expression datasets. Multivariate Cox proportional hazard regression analysis was used to select pathways associated with prognosis, and Pearson correlation analysis was used to investigate the association of prognosis-related pathways with immune microenvironment.Overall, 374 tumor samples and 50 adjacent normal samples from TCGA-LIHC database were incorporated in our research. We identified EMT-related lncRNAs by using the TCGA database and EMT gene database. Then, the differentially expressed EMT-related lncRNAs were selected by the comparison of tumor tissues with adjacent normal tissues, which included 478 upregulated lncRNAs and 14 downregulated lncRNAs  and validation set (n = 113) with the ratio of 7 : 3. We performed the univariate Cox regression analysis to select the EMT-related lncRNAs, which were associated with prognosis in the training set. 492 lncRNAs were determined for OS signature, and 480 lncRNAs were selected for RFS signature . As shown in Figures Based on the similarity of expression of EMT-related lncRNAs, the tability . A totaltability  and RFS tability  of clustTo further investigate the biomarkers for prognosis and tumorigenesis in HCC, we selected the tumorigenesis lncRNA which was simultaneously incorporated into OS prognostic model and RFS prognostic model. The Kaplan-Meier curves showed that patients with high expression of lnc-CCNY-1 had the unfavorable prognosis in both OS and RFS Figures . GSVA anTo further investigate the regulatory mechanism of lnc-CCNY-1, the radar chart was drawn to show the correlation with immune cells . The expThe pathogenesis of HCC was very complicated because occurrence resulted from several factors, including internal gene factors, external environment, and progress of chronic liver disease . BesidesEMT is a cellular program which played a crucial role for embryogenesis, wound healing, and malignant progression . In thisEMT-related lncRNAs were identified by using TCGA database and EMT gene base. Then, we selected the differentially expressed EMT-related lncRNAs by comparing the tumor tissues and adjacent normal tissues. Finally, nine lncRNAs were significantly associated with OS, and three lncRNAs were correlated with RFS. The risk scores of each patient were calculated by the coefficient and expression of aforementioned lncRNAs and further divided the patients with HCC into the high-risk group and low-risk group. In training set, Kaplan-Meier curves showed the favorable prognosis of OS and RFS in the low-risk group. The ROC curves and AUC values in both prognostic models indicated the discriminative value in both prognostic models. In line with the conclusion in the training set, the same results of Kaplan-Meier curves and high accuracy of prognostic models were shown in the validation set.In recent years, TME had received more attention due the immunotherapy had showed curative effect in cancer management. TME acted a critical role in tumor progression and affected the effect of immunotherapy. To investigate the association between EMT-related lncRNAs with TME, “Consensus Cluster Plus” package was used to generate two clusters of HCC cohort. The Kaplan-Meier curves in our study showed that OS and RFS of cluster C1 were longer than those of cluster C2. The differences between two clusters in terms of stromal score, ESTIMATE score and immune score, indicate that EMT-related lncRNAs may affect tumor progression by regulating TME. A previous study performed by Peng et al.  demonstrTo further investigate the biomarkers for prognosis and tumorigenesis in HCC, lnc-CCNY-1 which was simultaneously incorporated into OS prognostic model and RFS prognostic model was identified in our research. The expression of lnc-CCNY-1 was negatively with progression in terms for OS and RFS, indicating lnc-CCNY-1 may promote tumor progression of HCC. GSVA analysis showed that lnc-CCNY-1 was negatively associated with PPAR signaling pathway and positively correlated with CELL cycle pathway. Previous studies had reported that PPAR signaling pathway was downregulated in colorectal cancer and non-small-cell lung cancer , 49. HowIt was noted that our study also included several limitations. Firstly, the EMT-related lncRNA prognostic model was generated by bioinformatic approaches, which is not validated in our registers. Besides, lnc-CCNY-1 was identified as the key EMT-related lncRNA, which was not verified in in vivo or further in vitro experiment in this study. We plan to further investigate the mechanism of lnc-CCNY-1 for HCC in next research.Two EMT-related lncRNA prognostic models of OS and RFS were constructed to discriminate patients and predict prognosis of HCC. EMT-related lncRNAs may play a role on prognosis of HCC by influencing the immune microenvironment. Lnc-CCNY-1 was selected as the key EMT-related lncRNA for further research.


Background: This study aimed to examine the effects of a 12-week multicomponent mobile app-delivered intervention, the Meru Health Program (MHP), on mental health quality of life (QoL) and loneliness among the middle-aged and older adults with depression symptoms.Methods: The eligible participants  were enrolled in the MHP, a therapist-supported mobile intervention. Using a non-randomized pre-post design, change in mental health QoL [WHO QoL Brief (WHOQOL-BREF) psychological health] and loneliness  from baseline to post-treatment were examined. Time of enrollment [pre- vs. post-coronavirus disease 2019 (COVID-19)] was included as a between-subjects factor in the repeated measures analyses.Results: Forty-two participants enrolled prior to the COVID-19 pandemic; eight enrolled after the pandemic began. Among the pre-COVID-19 enrollees, increase in mental health QoL, F = 12.61, p = 0.001, η2 = 0.25 and decreases in loneliness emerged, F = 5.42, p = 0.025, η2 = 0.13. The changes in mental health QoL, but not loneliness, held for the combined sample, such as post-COVID-19 enrollees, F = 6.02, p = 0.018, η2 = 0.12. The regression analyses showed that increases in mindfulness were associated with the increased mental health QoL and decreased loneliness.Conclusion: Therapist-supported digital mental health interventions, such as the MHP, have the potential to improve mental health QoL and decrease loneliness among the middle-aged and older adults. The findings for loneliness may not hold during the periods of mandated isolation. Instead, therapists supporting digital interventions may need to tailor their approach to target loneliness. Loneliness, a subjective feeling of social isolation, afflicts more than a third 35%) of adults aged 45 and older . Further5% of aduThe interventions targeting loneliness primarily focus on the enhancing social skills, providing social support, increasing social access, and/or targeting maladaptive thoughts . The metAligned with the previous findings of the importance of addressing loneliness, the potential benefits of utilizing technology to promote social connectedness, and the inherent social connectedness in group interventions, we examined whether a multicomponent digital intervention may decrease loneliness. The digital intervention [Meru Health Program (MHP)] is a therapist-supported program that incorporates mindfulness and cognitive behavioral interventions to decrease depression and anxiety. Furthermore, the MHP is delivered in a group format with opportunities for social support through the therapist-moderated discussion among the group participants. Our previous work with middle-aged and older adults has demonstrated that the 8-week MHP program led to significant reductions in anxiety and depression  and subjThe present study aimed to extend previous findings on the benefits of the MHP on reducing depressive and anxiety symptoms to two important domains: QoL and loneliness. This study had two aims, which were to examine whether participation in the MHP resulted in change in (1) mental health QoL and (2) loneliness in a sample of middle aged and older adults with the depressive symptoms. In an exploratory aim, we investigated whether change in mindfulness was associated with change in mental health QoL and loneliness.This study was a 12-week non-randomized pre-post examination of the MHP in middle-aged and older adults .Recruitment of the participants occurred between April 2019 and March 2020 and between August 2020 and October 2020. The advertisements consisted of flyers posted on public community boards, newspaper advertisements, and digital advertisements (Craigslist and Facebook) targeting people aged 40 years and older within the California Bay Area. During the COVID-19 pandemic, digital ads on Craigslist and Facebook linked to a secure online contact survey became the primary source of recruitment between August and September 2020.The eligible participants were the residents from California, with a smartphone capable of running the MHP app, and had increased depressive symptoms defined as Patients Health Questionnaire nine-item Scores ≥7 . ExclusAt baseline, the participants completed a demographics and health questionnaire that collected information about race/ethnicity, marital status, living situation, education, general health information, and eight health conditions . Health conditions were tallied to create a variable capturing the total number of current health conditions.At baseline, a trained study personnel completed a brief semi-structured psychiatric diagnostic interview, the MINI , with thThe PHQ-9  is a 9-iThe Cognitive and Affective Mindfulness Scale-Revised CAMS-R  is 10-itDeveloped by the WHO, the WHO QoL-Brief (WHOQOL-BREF) , has a tThe University of California, Los Angeles (UCLA) Loneliness Scale  is a 20-item measure of subjective feelings of loneliness and social isolation. The items are scored based on the frequency with which respondents perceive each statement to be self-descriptive. The scores range from one (never) to four (often), with higher scores indicating greater loneliness. The UCLA Loneliness Scale is shown to have good psychometric properties, such as high internal consistency, test-retest reliability, convergent validity, and construct validity . The participants completed questionnaires and partook in a semi-structured psychiatric interview (MINI). At the end of the baseline assessment, the eligible participants were provided with a brief overview of the MHP enrollment process. After the visit, a research team member referred the participant to Meru Health for MHP enrollment. The MHP therapist or clinical coordinator set up a time for the participant to have a brief intake call with the therapist. The participant completed standard questionnaires as part of the Meru Health intake process. The week prior to each group starting, the participants received an email with instructions to download the app and a unique link to sign into the app.After determining eligibility through the telephone screen, the participants attended a baseline visit . App content is delivered in the weekly themes that address topics, such as mindfulness, thinking traps, self-compassion, values, sleep, and nutrition. Additional program features include therapist , and anonymous peer support from other group members. The therapist uses a dashboard to oversee the MHP progress of a patient. The therapist interacts with the patients by sending weekly informational emails, asynchronous secure messaging within the app, and conducting phone/video calls when needed. The peer support consists of therapist-moderated discussions that allow the group members to anonymously share thoughts and experiences with the practices. The group members can respond to each other comments by selecting from a menu of pre-determined responses .” Beyond this study, MHP is available in the United States and Finland through employer-based wellness plans, insurance, and university-based mental health clinics.n = 29; by phone/internet surveys n = 17).The PHQ-9 and CAMS-R measures were collected at weeks 5 and 9 by phone or through secure online surveys according to the preference of participants. The measures, such as PHQ-9, CAMS-R, WHOQOL-BREF, and UCLA Loneliness Scale were completed after the participants finished the 12-week MHP  and loneliness  for the pre-COVID-19 enrollees first. Next, these analyses were conducted with the entire sample, such as time of enrollment (pre- vs. post-COVID-19) as a between-subjects factor. Alpha was set at 0.05. The uncontrolled effect sizes using hedge's g were calculated.t-tests assessed whether the changes were significantly different from zero. Second, the linear regression analyses examined whether the baseline variables were associated with change in the dependent variables . Third, the linear regression analyses examined whether change in depression (PHQ-9) or mindfulness (CAMS-R) were associated with change in dependent variables .Correlates of change were examined in the exploratory analyses. Change scores in mental health QoL were calculated by subtracting the baseline score from the post-treatment scores. For mental health QoL, positive change indicates improvements , whereas for UCLA Loneliness scores, negative change indicates decrease in loneliness . First, single-sample SD = 11.26; range: 40–81 years) were enrolled in the MHP. About 60% (n = 30) of enrollees were female and the majority were white, non-Hispanic , followed by Asian , and Black/African American individuals . Mean baseline PHQ-9 scores were 12.28 (SD = 5.47) and fell in the moderate depressive symptom range (10–14). Regarding the baseline psychiatric diagnoses, two-thirds (66.7%) had either current major depressive disorder , an anxiety disorder , or both major depressive disorder and an anxiety disorder . Among the remaining third of participants, 19% (n = 8) had another current psychiatric disorder and 14% (n = 7) did not have any current psychiatric disorders. Fifty-four participants completed the baseline assessments; two were excluded (due to ineligibility) and two withdrew (due to improved symptoms and privacy concerns) prior to their MHP group start date (as shown in 2(50) = 5.36, p = 0.021], have lower baseline depression scores , and have higher baseline QoL-environment subscale scores , than post-COVID-19 enrollees. No baseline differences in mental health QoL or loneliness emerged.Data collection and enrollment intersected with the historical event of the onset of the COVID-19 pandemic, which brought about shelter-in-place restrictions. Forty-two participants enrolled prior to the COVID-19 pandemic; eight enrolled after the pandemic had begun. The pre-COVID-19 enrollees were more likely to be married or partnered , which demonstrated that the mental health QoL for the pre-COVID-19 enrollees was higher than that of post-COVID-19 enrollees  = 0.09, p = 0.770, η2 = 0.002], suggesting that the increased mental health QoL were similar for pre- and post-COVID-19 enrollees.A repeated measures ANOVA examined change in mental health QoL among the participants who enrolled in the MHP pre-COVID-19. Significant increase in mental health QoL as measured with the WHOQOL-BREF psychological health subscale were found with a significant main effect of time, F = 5.42, p = 0.025, η2 = 0.13. The uncontrolled effect size estimated using hedge's g was −0.24. A second analysis conducted with the combined sample of participants enrolled pre- and post-COVID-19 found no significant main effects for time  or enrollment . Moreover, the interaction was not significant,  and for loneliness [t(38) = −2.33, p = 0.025). When including the post-COVID-19 enrollees, only mental health QoL was significantly different from zero. Consequently, the linear regression analyses focused on the pre-COVID-19 sample that displayed significant change in the dependent variables from baseline to post-treatment. Next, we conducted a regression model that included the baseline factors  as the independent variables. This analysis was not significant, indicating that the baseline factors were not significant correlates of change in QoL or loneliness (results not shown). Then, we examined whether change in the depression symptoms (PHQ-9) and in mindfulness (CAMS-R) from baseline to post-treatment were predictors of change in QoL and in loneliness. As displayed in p = 0.004) and a negative association with loneliness . Change in the depressive symptoms had a negative association with mental health QoL that approached significance . Change in the depressive symptoms were significantly and positively associated with loneliness .The initial step in examining correlates of change was to determine whether the change scores significantly differed from zero. For the pre-COVID-19 sample, change was significantly different from zero for both mental health QoL [These findings show that the MHP, a therapist-supported digital mental health intervention, was associated with increased mental health QoL and decreased loneliness among the middle-aged and older adults in a non-randomized pre-post study. Notably, the improvements in mindfulness across treatment were associated with increased mental health QoL and decreased loneliness. In contrast, the declines in depression symptoms only corresponded to the declines in loneliness. Taken together, these findings suggest that one mechanism through which the MHP may impact loneliness and mental health QoL is by improving mindfulness. The finding that the mindfulness component of this intervention may reduce the subjective experience of loneliness dovetails with findings of a recent dismantling study that demonstrated that the combination of present focus and acceptance skills from mindfulness resulted in the declines in loneliness compared with present focus alone . NonjudgAlthough the future controlled studies need to replicate these findings, this investigation extends prior findings that support the reductions in psychiatric symptoms , 29–31 tLoneliness negatively impacts physical, cognitive, and mental health and longevity, particularly among the middle-aged and older adults –6. Thus,One important caveat to these findings is that when a historical event (COVID-19 pandemic) occurred, initiating shelter-in-place requirements for many participants, the decline in loneliness no longer held. The increase in mental health QoL remained significant regardless of shelter-in-place status, which highlights the potential benefits of using the digital mental health interventions for the middle-aged and older adults. It is possible that restricting opportunities to socialize in person cannot be overcome by the digital mental health interventions that otherwise have the potential to decrease loneliness. Therapists supporting the mobile health  interventions may need to tailor their approach during the COVID-19 pandemic by encouraging the patients to make video calls and explore possibilities of online interest groups and virtual meet-ups in order to mitigate loneliness. The group support aspect of the MHP has the potential to help participants with the feelings of loneliness and subjective isolation in their mental health-related struggles; however, our previous work has demonstrated that this component was deemed to be less helpful than the information provided within the app, the daily practices, and support of the therapists . In contSeveral limitations should be noted. First, this study lacked a control condition, thereby preventing any analyses or conclusions regarding the effect of the MHP on mental health QoL or loneliness compared with other interventions. As our study was not a dismantling study, it is possible that other MHP intervention components, such as behavioral activation, could have led to these improvements as well. Second, our findings are limited by the small number of enrollees after the COVID-19 shelter-in-place restrictions were enacted. Third, a measurement of objective social isolation was not obtained, thus limiting the interpretation of the findings, particularly with regard to the differences among the pre-COVID-19 and post-COVID-19 enrollees. Fourth, the sample was relatively homogeneous, consisting of white, non-Hispanic individuals, thus limiting information that can be gleaned about the effects of MHP among other groups. Fifth, our study was limited to the participants who had access to a smartphone, thus potentially limiting generalizability of the findings to those with higher technology proficiency and higher socioeconomic status .Despite these limitations, this investigation provides preliminary support for the effect of a therapist-supported mHealth intervention on yielding mental-health related QoL benefits, such as reduced loneliness. The regression analyses suggest that the components of MHP targeting mindfulness may be particularly important in yielding these mental health benefits. This study further demonstrates that older adults may benefit from the digital mental health interventions, which may, in turn, increase their access to mental healthcare. Future studies are needed to examine whether tailored therapist support targeting loneliness may enhance the effects of digital mental health interventions on this growing problem.cegould@stanford.edu.The datasets presented in this article are not readily available because data will be available upon reasonable request with agreement from funder. Requests to access the datasets should be directed to Christine Gould, The studies involving human participants were reviewed and approved by Stanford University Institutional Review Board. The patients/participants provided their written informed consent to participate in this study. During the COVID-19 pandemic, participants provided oral consent upon reviewing an informed consent document.CG conceptualized the research question, designed the study, oversaw data collection, conducted analyses, and drafted the manuscript. CCa collected data and assisted with drafting of the manuscript. AA assisted with drafting the manuscript. CCh assisted with data collection and with editing the manuscript. MB and VF-H edited the manuscript. All authors contributed to the article and approved the submitted version.Meru Health, Inc provided funding for this project. CG is supported by a Career Development Award (IK2 RX001478) from the Department of Veterans Affairs Rehabilitation Research and Development Service. The Stanford REDCap platform is developed and operated by the Stanford Medicine Research IT team. The REDCap platform services at Stanford are subsidized by (a) the Stanford School of Medicine Research Office and (b) the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, and through grant UL1 TR001085.Views expressed in this article are those of the authors and not necessarily those for the Department of Veterans Affairs or the Federal Government.The study received funding from Meru Health, Inc. The funder had no role in study design, data collection and analysis, or decision to publish. The funder's Chief Research Officer VF-H was a co-author on the study and assisted with editing the manuscript. VF-H receives salary from the company and owns options of the company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Post-hospital discharge follow-up has been a principal intervention in addressing gaps in care pathways. However, evidence about the willingness of primary care providers to deliver post-discharge follow-up care is lacking. This study aims to assess primary care providers’ preferences for delivering post-discharge follow-up care for patients with chronic diseases. Methods: An online questionnaire survey of 623 primary care providers who work in a hospital group of southeast China. Face-to-face interviews with 16 of the participants. A discrete choice experiment was developed to elicit preferences of primary care providers for post-hospital discharge patient follow-up based on six attributes: team composition, workload, visit pattern, adherence of patients, incentive mechanism, and payment. A conditional logit model was used to estimate preferences, willingness-to-pay was modelled, a covariate-adjusted analysis was conducted to identify characteristics related to preferences, 16 interviews were conducted to explore reasons for participants’ choices. Results: 623 participants completed the discrete choice experiment . Composition of the follow-up team and adherence of patients were the attributes of greatest relative importance with workload and incentives being less important. Participants were indifferent to follow-up provided by home visit or as an outpatient visit. Conclusion: Primary care providers placed the most importance on the multidisciplinary composition of the follow-up team. The preference heterogeneity observed among primary care providers suggests personalized management is important in the multidisciplinary teams, especially for those providers with relatively low educational attainment and less work experience. Future research and policies should work towards innovations to improve patients’ engagement in primary care settings. Chronic diseases have been the predominant challenge worldwide as a result of the epidemiological transition, rapid population aging, and fragmented healthcare systems ,2. IntegChina has developed and implemented people-centered integrated healthcare systems in the last decade ,11. In aParticipants’ perspectives should be considered in designing follow-up programs for discharged patients, in order to improve feasibility, acceptability, and effectiveness. Some studies have explored patients’ preferences for cancer post discharge follow-up care using discrete choice experiments (DCEs) or best-worst scaling (BWS), with inconsistent results. Gulliford et al. compared experiences of 193 UK patients with breast cancer, who were randomized to receive either conventional intensive follow-up or less intensive follow-up, to find that women appeared to prefer non-intensive follow-up schedules . AnotherWe aimed to elicit preferences of providers in primary care settings for follow-up of discharged patients using a discrete choice experiment. Moreover, as socio-demographic or work-related characteristics may have some effect on providers’ preferences, we further analyzed the influence of these characteristics over preferences for different follow-up team compositions in order to provide insight for policy making in the 4000+ district/county medical consortia about follow-up of discharged patients in integrated primary care settings of China and other countries.Yangxi County is located on the southwest coast of Guangdong Province, China. In order to promote integrated care, Yangxi Hospital Group (YHG) was established in 2017, consisting of three county-level hospitals and eight township health centers (THCs). YHG is planning to provide follow-up care for discharged patients with diabetes and hypertension to promote the integration of care. Based on the EEPHS program, all patients with diabetes and hypertension in Yangxi county are managed in the Integrated Care System for patients with Chronic Diseases (ICSCD). According to the existing implementation plan, once a patient with diabetes or hypertension is discharged from one of the three county-level hospitals, the patient is placed on the follow-up list of the THC where the patient lives. The patient’s healthcare record and sociodemographic information is shared among providers in hospitals and THCs and the patient is followed-up within seven days of discharge. Data collected at the follow-up is shared in the ICSCD, and follow-ups are repeated every week, four weeks, or twelve weeks according to risk status of the patient. However, there is little evidence available on motivating primary care providers to participate in the follow-ups.Cluster sampling was used in this study. All physicians, nurses and other providers working in the eight THCs of YHG were invited to participate in a web-survey. The survey was conducted in November 2020, after China managed to control COVID19. Participation in the survey was voluntary with a consent form. Participants were not compensated. In addition, 2 providers in each THC were purposively sampled and interviewed about reasons underlying the choices made. This study (No. 2020-114) was approved by the Ethical Commission of School of Public Health, Sun Yat-Sen University. n = 8) with researchers working on primary care and a focus group discussion with 2 physicians, 2 nurses, and 2 public health physicians from three THCs in YHG. Eventually, six attributes, including team composition, workload, follow-up pattern, adherence of patients, incentives, and payments, were included in this study. In this study, the attributes and levels for the DCE were chosen based on literature reviews, key informant interviews , based on regression results using Stata’s nlcom command. In this study, the WTP for a higher level of a specific follow-up group attribute All statistical analyses were performed using STATA 14.0. Interviews with 16 providers were transcribed word by word, and thematic analysis was conducted by MAXQDA 11.All health workers in the eight THCs of YHG were invited to participate in the web-survey and 623 agreed to participate (response rate 86.40%). Since diabetes and hypertension may lead to vascular complications, which are major causes of mortality and morbidity in the long term, appropriate follow-up for discharged patients is critical to reduce complications and increase patient quality of life ,22. TakiThe results suggest that providers in primary care settings preferred a follow-up team with higher payments, multidisciplinary team members, less workload, incentive mechanisms without penalties, and good adherence of patients. They prioritized composition of the follow-up team when deciding which team to take part in. This was further supported by the results of willingness to pay analysis and face-to-face interviews with health workers. Health workers were willing to give up ¥1.673 or ¥2.282 of payment per follow-up visit respectively to join a regular team  or an advanced team  as compared to a basic team . Multidisciplinary teams offer several advantages over individual providers. A multidisciplinary team is better placed to meet the physical and mental demands of patients, especially those with multiple chronic diseases and combined medication. In addition, a multidisciplinary team offers a supportive structure in which team members offer each other coaching, encouragement, mentorship, and discipline . MultidiAdherence of patients, workload and incentives were of less importance than team composition. Analysis of willingness to pay showed that health workers were willing to give up ¥1.442 of payment per follow-up visit to join a team with good patient adherence and require additional compensation of ¥1.310 per follow-up visit for them to accept serving 20–40 more patients per month. Different from results of research from patients’ perspectives, multi-providers in this study pay no attention to location of the follow-up care ,31. TherThe analysis with interaction terms found significant variation in preferences based on providers’ educational attainment. Providers with high educational attainment place a much higher importance on multidisciplinary team members and home visits. In contrast providers with low educational attainment placed a lower value on a mechanism with penalties. Additionally, gender and working time also have impacts on providers’ preferences. Male participants valued multidisciplinary teams more than female participants, and providers with less work experience considered good patient adherence more important than more experienced providers. This information provides insights on matching team members based on their characteristics.Health care systems with high-performing primary care systems achieve better processes of care, better health outcomes and lower overall health care expenditure ,34. PrimThe first and most important feature of implementing post discharge follow up care is to arrange multidisciplinary follow-up teams with GPs, nurses, public health physicians, pharmacists, health managers, nutritionists, and other health care providers. According to the experience of multi-disciplinary teams (MDTs) in specialist hospitals, joint training and regular or non-regular team meetings promote capacity building and interdisciplinary cooperation in the follow-up teams . Second,To our knowledge, this is the first stated preference study to explore primary care providers’ preferences towards follow-up care of discharged patients with chronic diseases. The study design, DCE, quantifies individuals’ priorities by estimating the relative importance of different attributes. Moreover, the results provide evidence of how to implement follow-up teams and how to optimize care processes. This informs policy-making processes concerning integrated care for patients with chronic diseases in the district/county medical consortia in China and health care systems in other countries.However, this study is subject to some limitations. First, the data were collected through online questionnaires, and the cognitive ability of each participant with respect to completing the task was not evaluated. Participants completing the online questionnaire are likely to be younger, have more education, and possess higher cognitive ability than general primary care providers overall. Although providers participating in the face-to-face interviews showed good cognitive ability about making choices, the web-survey might ignore preferences of older primary care providers. Second, the three levels of the follow-up visit pattern were not highly differentiated. In other research on patient preferences, telephone follow up, home visit, and outpatient visits were compared . We defiFollow-up of patients following hospital discharge is an important part of integrated care for patients with chronic diseases. Our overall results suggest that primary care providers placed the most importance on having a multidisciplinary follow-up team. To further improve efficiency and quality of follow-up care, personalized management is suggested in the multidisciplinary teams, especially for those providers with relatively low educational attainment and less work experience. This study not only makes a contribution to developing policies on implementing post-discharge follow-up, building multidisciplinary teams, and promoting care integration in the over 4000 district/county medical consortia in China, but also provides a methodology for exploring providers’ preferences for models of care delivery in health care systems of other countries.


The safety of active surveillance (AS) in favorable intermediate-risk (FIR) prostate cancer (PCa) remains uncertain. To provide guidance on clinical decision-making, we examined long-term and pathological outcomes of low-risk and intermediate-risk PCa patients after radical prostatectomy (RP).The study involved 5693 patients diagnosed between 1994 and 2019 with low-risk, FIR, and unfavorable intermediate-risk (UIR) PCa (stratification according to the AUA guidelines) who underwent RP. Pathological outcomes were compared, and Kaplan–Meier analysis determined biochemical recurrence-free survival (BRFS) and cancer-specific survival (CSS) at 5, 10, 15, and 20 years. Multiple Cox regression was used to simultaneously control for relevant confounders.p < 0.001; 19.8% vs. 12.0%, p < 0.001) as well as pathological tumor and node stage  compared to patients at low risk. The 20-year BRFS was 69%, 65%, and 44% and the 20-year CSS was 98%, 95%, and 89% in low-risk, FIR, and UIR patients. On multiple Cox regression, FIR was not associated with a worse BRFS , UIR was associated with a worse BRFS .Those at FIR had higher rates of upgrading and upstaging (12.8% vs. 7.2%, Patients at FIR had only slightly worse pathological and long-term outcomes compared to patients at low risk, whereas the difference compared to patients at UIR was large. This emphasizes AS in these patients as a possible treatment strategy in well-counseled patients.The online version contains supplementary material available at 10.1007/s00345-021-03717-2. Active surveillance (AS) has become a widely accepted standard of care in low-risk prostate cancer (PCa) to reduce overtreatment and associated morbidity. AS offers the benefit of preservation of quality of life while retaining the assurance of definitive treatment if required. Cancer-specific survival (CSS) rates of AS in low-risk PCa have been reported to be consistent with those of radiation therapy or surgery , 2. The To address this void and provide guidance on selecting FIR PCa patients for AS, this study examined long-term outcomes up to 20 years, comprising biochemical recurrence-free survival (BRFS), CSS and adverse surgical pathology, for low-risk and FIR PCa patients after RP, controlling for relevant confounders, including a detailed family history of cancer.Analyses were based on the nationwide multicenter German Familial Prostate Cancer prospective study, which has surveyed newly diagnosed patients with PCa independent of family history since 1994 , 15. InfSociodemographic and clinical data included age at surgery, family history of PCa , whereas the difference to UIR was still very large [18% (65% vs. 43%)]. When adjusting for other relevant factors in the multiple Cox regression analysis, FIR PCa was not associated with a worse BRFS . In contrast, UIR PCa was associated with a worse BRFS , which shows that a difference clearly exists between FIR and UIR. This is in line with findings of Aghazadeh et al. investigating a shorter follow-up of 3686 patients after RP. After controlling for year of surgery, FIR did not differ significantly from patients at low risk; however, UIR PCa was associated with a worse 5-year BRFS .p < 0.001] and , respectively. However, CSS rates of FIR were closer to low-risk than to UIR PCa patients. Once again, this emphasizes the existence of FIR as an own risk group and the feasibility of AS in the well-counseled patient. Moreover, after adjusting for other factors neither FIR nor UIR was associated with a worse CSS. In the AS screening arm of the Göteborg trial, CSS at 15 years was lower for the intermediate-risk group compared to our results (90% vs. 97%); however, they did not distinguish between FIR and UIR, explaining the different results [In the current study, CSS at 15 and 20 years was high among all three subgroups [99% (low risk) vs. 97% (FIR) vs. 91% (UIR);  results . In the The current study provides additional data that a positive family history or a fatal family history of PCa is not associated with a higher risk of worse long-term outcomes, i.e., BRFS and CSS, respectively, in FIR PCa patients. Additionally, recent data from a cross-sectional study of our own group indicated no detrimental effect of a positive family history on postoperative upgrading and upstaging in FIR PCa . Thus, pIn the current analysis, we observed a significant difference in adverse pathological features between patients at low risk and those at FIR; however, long-term outcomes revealed only slight differences between them. On the other hand, differences between FIR and UIR were very large supporting different treatment strategies between these groups such as AS. However, patients must be informed that the evidence supporting definitive treatment is more robust compared to AS. Additionally, patients should be aware of that when AS is selected as first-line management strategy, a considerable amount of men with FIR eventually proceed with definitive treatment the following years. However, there is evidence that a period of AS does not result in worse outcomes compared to patients undergoing up-front RP . FinallyLimitations of the current study include its retrospective nature and that data were derived from a RP cohort so that results may be subject to selection bias. Furthermore, there was not a central pathology review of the biopsy and prostatectomy specimen increasing the risk of inter-observer variation of pathological features. In addition, our database does not provide information about the use of preoperative mpMRI and targeted biopsies in our patient population. This might lead to increased rates of upgrading and upstaging compared to patients diagnosed with mpMRI and targeted biopsies. Therefore, we additionally assessed whether stage and grade migration changed over the study period trying to investigate indirectly the impact of modern diagnostic pathways implemented in the past decade. However, stage and grade migration even increased toward non-organ confined disease/lymph node invasion and higher GG over the study period suggesting that the use of additional mpMRI might be low in the current sample and that there are other unknown factors leading to these increased rates. Furthermore, it should be kept in mind when interpreting results of the current analysis that a patient of a certain risk group in the modern era might differ from one diagnosed one or even two decades ago, particularly in the method of diagnosis. Eventually, data such as perineural invasion, number of positive cores, percentage PCa in a core, and PSA density were lacking and not included in the analysis. Despite these limitations, our data provide important information about long-term outcomes of low-risk, FIR, and UIR PCa patients in a large nationwide, population-based sample with verified, complete, and detailed information about family history of PCa. Nowadays, use of contemporary technology including genomics and mpMRI is steadily increasing and may refine risk stratification, especially in the intermediate-risk group.Results of the current study indicated that FIR PCa patients are more likely to have worse pathological outcomes compared to those at low risk. However, the absolute differences are small- and long-term outcomes differed only slightly between low-risk and FIR PCa patients, whereas the difference between FIR and UIR was very large. This emphasizes the role of AS in FIR PCa patients as an appropriate treatment strategy in the well-counseled patient. Nevertheless, shared decision-making and adequate patient counselling have the key role in reaching the best decision for each patient.Supplementary file1 (DOCX 17 KB)Below is the link to the electronic supplementary material.