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The NCCN Guidelines for Survivorship are intended to help healthcare professionals address the complex and varied needs of cancer survivors. The NCCN Guidelines provide screening, evaluation, and treatment recommendations for psychosocial and physical problems resulting from adult-onset cancer and its treatment; recommendations to help promote healthy behaviors and immunizations in survivors; and a framework for care coordination. These NCCN Guidelines Insights summarize recent guideline updates and panel discussions pertaining to sleep disorders, fatigue, and cognitive function in cancer survivors.

In the context of autosomal dominant polycystic kidney disease (ADPKD), measurement of the total kidney volume (TKV) is crucial. It acts as a marker for tracking disease progression, and evaluating the effectiveness of treatment strategies. The TKV has also been recognized as an enrichment biomarker and a possible surrogate endpoint in clinical trials. Several imaging modalities and methods are available to calculate the TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess the cyst burden, which can be crucial to assessing the disease state and helping to identify rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond these measurements, the quantification and characterization of non-cystic kidney tissue shows potential for stratifying ADPKD patients early on, monitoring disease progression, and possibly predicting renal function loss. A broad spectrum of radiological imaging techniques are available to characterize the kidney tissue, showing promise when it comes to non-invasively picking up the early signs of ADPKD progression. Radiomics have been used to extract textural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging biomarkers, focusing on the quantification methods, potential, and necessary steps toward a successful translation to clinical practice.

Congenital disorders of glycosylation (CDG) and mitochondrial disorders are multisystem disorders with overlapping symptomatology. Pathogenic variants in the PMM2 gene lead to abnormal N-linked glycosylation. This disruption in glycosylation can induce endoplasmic reticulum stress, contributing to the disease pathology. Although impaired mitochondrial dysfunction has been reported in some CDG, cellular bioenergetics has never been evaluated in detail in PMM2-CDG. This prompted us to evaluate mitochondrial function and autophagy/mitophagy in vitro in PMM2 patient-derived fibroblast lines of differing genotypes from our natural history study. We found secondary mitochondrial dysfunction in PMM2-CDG. This dysfunction was evidenced by decreased mitochondrial maximal and ATP-linked respiration, as well as decreased complex I function of the mitochondrial electron transport chain. Our study also revealed altered autophagy in PMM2-CDG patient-derived fibroblast lines. This was marked by an increased abundance of the autophagosome marker LC3-II. Additionally, changes in the abundance and glycosylation of proteins in the autophagy and mitophagy pathways further indicated dysregulation of these cellular processes. Interestingly, serum sorbitol levels (a biomarker of disease severity) and the CDG severity score showed an inverse correlation with the abundance of the autophagosome marker LC3-II. This suggests that autophagy may act as a modulator of biochemical and clinical markers of disease severity in PMM2-CDG. Overall, our research sheds light on the complex interplay between glycosylation, mitochondrial function, and autophagy/mitophagy in PMM2-CDG. Manipulating mitochondrial dysfunction and alterations in autophagy/mitophagy pathways could offer therapeutic benefits when combined with existing treatments for PMM2-CDG.

Objectives: Desirable outcomes following surgery for anterior shoulder instability (ASI) include a multitude of functional and clinical functions, yet it remains uncertain if all of these outcomes are simultaneously achievable (i.e. can patients have full motion and no instability; does excellent stability coincide with stiffness?). The purpose of this study was to employ unsupervised machine learning techniques to define the actual "optimal observed outcome” for patients undergoing surgical treatment for ASI and to identify predictors of obtaining this outcome. Methods: Patients <40 years with an initial diagnosis of ASI from 1994 -2016 were included. Four unsupervised machine learning clustering algorithms were evaluated to partition subjects into “optimal observed outcome” or “suboptimal outcome” based on combinations of actually observed outcomes. Demographic, clinical, and treatment variables were compared between groups using descriptive statistics and Kaplan-Meier survival curves; multivariate stepwise logistic regression evaluated variable prognostic value. Results: 200 patients with a mean follow-up of 11 years were included. 146 (64%) obtained the “optimal observed outcome”, characterized by significantly (P <0.001) lower rates of: recurrent postoperative pain (23% vs 52%), recurrent instability (12% vs 41%), revision surgery (10% vs 24%), progression to osteoarthritis (OA) (5% vs. 19%), and mildly restricted motion (161° vs. 168°). Stepwise multivariate logistic regression identified time from initial instability to presentation (OR: 0.96, 95% CI: 0.92-0.98) and habitual instability (OR: 0.17, 95%CI: 0.04-0.77) as negative predictors of “observed optimal outcome”. Increased rate of subluxation over frank dislocation pre-operatively (OR: 1.30, 95% CI: 1.02-1.65) was a positive predictor. Type of surgery performed was not a significant predictor. Conclusions: Following surgical treatment for ASI, an appropriate “optimal observed outcome” can be defined as: minimal postoperative pain, absence of recurrent instability, low rates of revision surgery, absence of OA, and increased ROM. This “optimal observed outcome” was achieved in over 2/3rds of the cohort and this work demonstrated the synergistic relationship of these. The most significant predictors included shorter time to presentation and history of subluxations over frank dislocations pre-operatively. This definition of the “optimal observed outcome” may be more appropriate for surgical decision making and setting appropriate expectations. [Table: see text][Table: see text]

Abstract Rationale In addition to rare genetic variants and the MUC5B locus, common genetic variants contribute to idiopathic pulmonary fibrosis (IPF) risk. The predictive power of common variants outside the MUC5B locus for IPF and interstitial lung abnormalities (ILAs) is unknown. Objectives We tested the predictive value of IPF polygenic risk scores (PRSs) with and without the MUC5B region on IPF, ILA, and ILA progression. Methods We developed PRSs that included (PRS-M5B) and excluded (PRS-NO-M5B) the MUC5B region (500-kb window around rs35705950-T) using an IPF genome-wide association study. We assessed PRS associations with area under the receiver operating characteristic curve (AUC) metrics for IPF, ILA, and ILA progression. Measurements and Main Results We included 14,650 participants (1,970 IPF; 1,068 ILA) from six multi-ancestry population-based and case–control cohorts. In cases excluded from genome-wide association study, the PRS-M5B (odds ratio [OR] per SD of the score, 3.1; P = 7.1 × 10−95) and PRS-NO-M5B (OR per SD, 2.8; P = 2.5 × 10−87) were associated with IPF. Participants in the top PRS-NO-M5B quintile had ∼sevenfold odds for IPF compared with those in the first quintile. A clinical model predicted IPF (AUC, 0.61); rs35705950-T and PRS-NO-M5B demonstrated higher AUCs (0.73 and 0.7, respectively), and adding both genetic predictors to a clinical model yielded the highest performance (AUC, 0.81). The PRS-NO-M5B was associated with ILA (OR, 1.25) and ILA progression (OR, 1.16) in European ancestry participants. Conclusions A common genetic variant risk score complements the MUC5B variant to identify individuals at high risk of interstitial lung abnormalities and pulmonary fibrosis.

SummaryDespite the availability of evidence‐based interventions to improve binge eating, Black women have some of the lowest rates of access to care for eating disorders. Innovation is needed to offer accessible and culturally relevant treatment options. To this end, using an open trial design, we investigated the feasibility and acceptability of a group‐based, appetite awareness training (AAT) + lifestyle modification (LM) programme in Black women at risk for BED in a primary care setting. Participants (n = 20) were Black women recruited from a family medicine centre affiliated with a local public university, and who reported at least two binge eating episodes in the last 28 days. Participants completed a 16‐session AAT + LM programme over 4 months. Key outcomes were objective binge eating (assessed by the EDE and the EDE‐Q), body dissatisfaction, and weight change, all assessed at baseline, four (post‐treatment) and 6 months (2‐month follow‐up). Ninety‐five percent of participants completed assessments at post‐treatment and attended nearly 60% of intervention sessions. Among completers (n = 19), body dissatisfaction and objective binge eating decreased from baseline to post‐treatment and this decrease was maintained at the 2‐month follow‐up. In exit interviews, participants reported programme satisfaction. Providing training in appetite awareness combined with lifestyle modification principles may be useful in the treatment of body dissatisfaction and binge eating among Black women.

PURPOSE The investigation of multiple molecular targets with next-generation sequencing (NGS) has entered clinical practice in oncology, yielding to a paradigm shift from the histology-centric approach to the mutational model for personalized treatment. Accordingly, most of the drugs recently approved in oncology are coupled to specific biomarkers. One potential tool for implementing the mutational model of precision oncology in daily practice is represented by the Molecular Tumor Board (MTB), a multidisciplinary team whereby molecular pathologists, biologists, bioinformaticians, geneticists, medical oncologists, and pharmacists cooperate to generate, interpret, and match molecular data with personalized treatments. PATIENTS AND METHODS Since May 2020, the institutional MTB set at Fondazione IRCCS Istituto Nazionale Tumori of Milan met weekly via teleconference to discuss molecular data and potential therapeutic options for patients with advanced/metastatic solid tumors. RESULTS Up to October 2021, among 1,996 patients evaluated, we identified >10,000 variants, 43.2% of which were functionally relevant (pathogenic or likely pathogenic). On the basis of functionally relevant variants, 711 patients (35.6%) were potentially eligible to targeted therapy according to European Society of Medical Oncology Scale for Clinical Actionability of Molecular Targets tiers, and 9.4% received a personalized treatment. Overall, larger NGS panels (containing >50 genes) significantly outperformed small panels (up to 50 genes) in detecting actionable gene targets across different tumor types. CONCLUSION Our real-world data provide evidence that MTB is a valuable tool for matching NGS data with targeted treatments, eventually implementing precision oncology in clinical practice.

Purpose To use unsupervised machine learning clustering to define the “optimal observed outcome” after surgery for anterior shoulder instability (ASI) and to identify predictors for achieving it. Methods Medical records, images, and operative reports were reviewed for patients <40 years old undergoing surgery for ASI. Four unsupervised machine learning clustering algorithms partitioned subjects into “optimal observed outcome” or “suboptimal outcome” based on combinations of actually observed outcomes. Demographic, clinical, and treatment variables were compared between groups using descriptive statistics and Kaplan‐Meier survival curves. Variables were assessed for prognostic value through multivariate stepwise logistic regression. Results Two hundred patients with a mean follow‐up of 11 years were included. Of these, 146 (64%) obtained the “optimal observed outcome,” characterized by decreased: postoperative pain (23% vs 52%; P < 0.001), recurrent instability (12% vs 41%; P < 0.001), revision surgery (10% vs 24%; P = 0.015), osteoarthritis (OA) (5% vs 19%; P = 0.005), and restricted motion (161° vs 168°; P = 0.001). Forty‐one percent of patients had a “perfect outcome,” defined as ideal performance across all outcomes. Time from initial instability to presentation (odds ratio [OR] = 0.96; 95% confidence interval [CI], 0.92‐0.98; P = 0.006) and habitual/voluntary instability (OR = 0.17; 95% CI, 0.04‐0.77; P = 0.020) were negative predictors of achieving the “optimal observed outcome.” A predilection toward subluxations rather than dislocations before surgery (OR = 1.30; 95% CI, 1.02‐1.65; P = 0.030) was a positive predictor. Type of surgery performed was not a significant predictor. Conclusions After surgery for ASI, 64% of patients achieved the “optimal observed outcome” defined as minimal postoperative pain, no recurrent instability or OA, low revision surgery rates, and increased range of motion, of whom only 41% achieved a “perfect outcome.” Positive predictors were shorter time to presentation and predilection toward preoperative subluxations over dislocations. Level of Evidence Level IV, retrospective cohort.

PURPOSE The COVID-19 pandemic has profoundly affected cancer care worldwide, including radiation therapy (RT) for breast cancer (BC), because of risk-based resource allocation. We report the evolution of international breast RT practices during the beginning of the pandemic, focusing on differences in treatment recommendations between countries. MATERIALS AND METHODS Between July and November 2020, a 58-question survey was distributed to radiation oncologists (ROs) through international professional societies. Changes in RT decision making during the first surge of the pandemic were evaluated across six hypothetical scenarios, including the management of ductal carcinoma in situ (DCIS), early-stage, locally advanced, and metastatic BC. The significance of changes in responses before and during the pandemic was examined using chi-square and McNemar-Bowker tests. RESULTS One thousand one hundred three ROs from 54 countries completed the survey. Incomplete responses (254) were excluded from the analysis. Most respondents were from the United States (285), Japan (117), Italy (63), Canada (58), and Brazil (56). Twenty-one percent (230) of respondents reported treating at least one patient with BC who was COVID-19–positive. Approximately 60% of respondents reported no change in treatment recommendation during the pandemic, except for patients with metastatic disease, for which 57.7% (636/1,103; P < .0005) changed their palliative practice. Among respondents who noted a change in their recommendation during the first surge of the pandemic, omitting, delaying, and adopting short-course RT were the most frequent changes, with most transitioning to moderate hypofractionation for DCIS and early-stage BC. CONCLUSION Early in the COVID-19 pandemic, significant changes in global RT practice patterns for BC were introduced. The impact of published results from the FAST FORWARD trial supporting ultrahypofractionation likely confounded the interpretation of the pandemic's independent influence on RT delivery.

Drivers of the inflammatory response in acute pancreatitis remain incompletely understood. Unsaturated fatty acids, specifically palmitoleic, appear to have an association with more severe acute pancreatitis. This finding presents a new clinical understanding of fatty acid toxicity and highlights a potential future target for treatment in severe acute pancreatitis.