A thorough understanding of the tumor environment and underlying genetic factors helps in the better formulation of cancer management strategies. Availability of efficient diagnostic and prognostic biomarkers facilitates early detection and progression of the disease. MicroRNAs affect different biological processes participating in tumorigenesis through regulation of their target genes. An expanding list of unique RNAs and understanding of their regulatory role has opened up a new field in cancer research.Based on a comprehensive literature search, we identified 728 miRNAs dysregulated in sixteen cancer types namely bladder cancer (BC), breast cancer (BrC), cervical cancer (CC), colorectal cancer (CRC), esophageal cancer (EC), endometrial cancer (EnC), gastric cancer (GC), hepatocellular cancer (HCC), head and neck squamous cell cancer (HNSCC), lung cancer (LC), ovarian cancer (OC), pancreatic cancer (PC), prostate cancer (PrC), renal cell cancer (RCC), skin cancer (SC), and thyroid cancer (TC). Expression of 43 miRNAs was either upregulated or downregulated in six or more of these cancers. Finally, seven miRNAs namely mir-18a, mir-21, mir-143/145, mir-210, mir-218, mir-221, showing maximum dysregulation, either up-or down-regulation in the majority of cancers, were selected for a detailed presentation of their expression and evaluation of their potential as biomarkers in the diagnosis and prognosis of different cancers.

Background Nearly half of the patients with breast cancer experience clinically significant mental distress within the first year of receiving their cancer diagnosis. There is an urgent need to identify scalable and cost-efficient ways of delivering empirically supported mental health interventions to patients with breast cancer. Objective The aim of this study was to evaluate the feasibility of in-clinic recruitment for a mobile phone app study and to evaluate the usability and preliminary impact of a suite of mental health apps (IntelliCare) with phone coaching on psychosocial distress symptoms in patients recently diagnosed with breast cancer. Methods This pilot study adopted a within-subject, 7-week pre-post study design. A total of 40 patients with breast cancer were recruited at a US National Cancer Institute–designated clinical cancer center. Self-reported distress (Patient Health Questionnaire-4) and mood symptoms (Patient-Reported Outcomes Measurement Information System depression and anxiety scales) were assessed at baseline and postintervention. App usability was assessed at postintervention. Results The minimum recruitment threshold was met. There was a significant decrease in general distress symptoms, as well as symptoms of depression and anxiety, from baseline to postintervention. Overall, participants reported high levels of ease of app use and learning. Scores for app usefulness and satisfaction were reinforced by some qualitative feedback suggesting that tailoring the apps more for patients with breast cancer could enhance engagement. Conclusions There is a dire need for scalable, supportive interventions in cancer. The results from this study inform how scalable mobile phone–delivered programs with additional phone support can be used to support patients with breast cancer. International Registered Report Identifier (IRRID) RR2-10.2196/11452

Background Nearly half of newly diagnosed breast cancer patients will report clinically significant symptoms of depression and/or anxiety within the first year of diagnosis. Research on the trajectory of distress in cancer patients suggests that targeting patients early in the diagnostic pathway could be particularly impactful. Given the recent rise of smartphone adoption, apps are a convenient and accessible platform from which to deliver mental health support; however, little research has examined their potential impact among newly diagnosed cancer patients. One reason is likely due to the obstacles associated with in-clinic recruitment of newly diagnosed cancer patients for mHealth pilot studies. Methods This article draws from our experiences of a recently completed pilot study to test a suite of mental health apps in newly diagnosed breast cancer patients. Recruitment strategies included in-clinic pamphlets, flyers, and direct communication with clinicians. Surgical oncologists and research staff members approached eligible patients after a medical appointment. Research team members met with patients to provide informed consent and review the study schedule. Results Four domains of in-clinic recruitment challenges emerged: (a) coordination with clinic staff, (b) perceived burden among breast cancer patients, (c) limitations regarding the adoption and use of technology, and (d) availability of resources. Potential solutions are provided for each challenge. Conclusion Recruitment of newly diagnosed cancer patients is a major challenge to conducting mobile intervention studies for researchers on a pilot-study budget. To realize the impact of mobile interventions for the most vulnerable cancer patient populations, health researchers must address barriers to in-clinic recruitment to provide vital preliminary data in proposals of large-scale research projects.

Aim Remote follow‐up (RFU) after colorectal cancer (CRC) surgery allows delivery of surveillance tests without the need for regular outpatient clinical appointments. However, little is known about health‐related quality of life (HRQoL) in RFU patients. The main aim of this study was to quantify HRQoL in our RFU population to identify particular patient groups that may benefit from a more personalised approach to follow‐up, including access to a survivorship clinic. Method EQ‐5D, QLQ‐C30 and QLQ‐C29 questionnaires were distributed to CRC patients enrolled in a RFU programme. The primary outcome of HRQoL scores was analysed by year of RFU, demographics, operation type, stoma and adherence to RFU protocols. Results A total of 428 respondents were included, with a mean age of 71 years (SD 10.1 years) and a median RFU time of 2.6 years [interquartile range (IQR) 1.6–4.8 years]. ‘Perfect health’ was reported by 26.6% of patients. The median EQ‐5D index score was 0.785 (IQR 0.671–1) and the median QLQ‐C30 Global HRQoL score was 75 (IQR 58.3–83.3). Women had a significantly lower EQ‐5D median score of 0.767 (IQR 0.666–0.879, P = 0.0088). Lower QLQ‐C30 HRQoL scores were seen in stoma patients (median 66.6, IQR 58.3–83.3, P = 0.0029). Erectile dysfunction (P = 0.0006) and poor body image (P = 0.001) were also reported more frequently in stoma patients. Patients undergoing right‐sided resection reported a lower median EQ‐5D score of 0.765 (IQR 0.666–0.879, P = 0.028) and higher pain severity (P = 0.0367) compared with left‐sided resections. There were 128 (29.4%) patients who breached RFU protocol and were seen in ad hoc colorectal clinics. However, there was no statistical difference in HRQoL between patients who adhered to or breached RFU protocols. Conclusion Overall HRQoL in patients in RFU is good, with no difference in those strictly followed up remotely. However, women, patients with right‐sided resection and patients with a stoma may require additional clinical reviews.

We extend questionable research practices (QRPs) research by conducting a robust, large-scale analysis of p-hacking in organizational research. We leverage a manually curated database of more than 1,000,000 correlation coefficients and sample sizes, with which we calculate exact p-values. We test for the prevalence and magnitude of p-hacking across the complete database as well as various subsets of the database according to common bivariate relation types in the organizational literature (e.g., attitudes-behaviors). Results from two analytical approaches (i.e., z-curve, critical bin comparisons) were consistent in both direction and significance in nine of 18 datasets. Critical bin comparisons indicated p-hacking in 12 of 18 subsets, three of which reached statistical significance. Z-curve analyses indicated p-hacking in 11 of 18 subsets, two of which reached statistical significance. Generally, results indicated that p-hacking is detectable but small in magnitude. We also tested for three predictors of p-hacking: Publication year, journal prestige, and authorship team size. Across two analytic approaches, we observed a relatively consistent positive relation between p-hacking and journal prestige, and no relationship between p-hacking and authorship team size. Results were mixed regarding the temporal trends (i.e., evidence for p-hacking over time). In sum, the present study of p-hacking in organizational research indicates that the prevalence of p-hacking is smaller and less concerning than earlier research has suggested.