Abstract Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and C. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias). Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic.

Risk of bias in translational medicine may take one of three forms: A. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias), B. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and C. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias). Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic.

Background

Maintenance of function during cancer treatment is important to older adults. Characteristics associated with pretreatment life-space mobility and changes during non-small cell lung cancer (NSCLC) treatment remain unknown.

Methods

This mixed methods cohort study recruited adults age ≥65 with advanced NSCLC starting palliative chemotherapy, immunotherapy, and/or targeted therapy from a Comprehensive Cancer Center, Veterans Affairs, and safety-net clinic. Patients completed geriatric assessments including Life-Space Assessment (LSA) pretreatment and at 1, 2, 4, and 6 months after treatment initiation. LSA scores range from 0 to 120 (greater mobility); LSA <60 is considered restricted. We used mixed-effects models to examine pretreatment LSA, change from 0 to 1 month, and change from 1 to 6 months. A subgroup participated in semistructured interviews pretreatment and at 2 and 6 months to understand the patient experience of life-space change. For each interview participant, we created joint displays of longitudinal LSA scores juxtaposed with illustrative quotes.

Results

Among 93 patients, median age was 73 (range 65-94). Mean pretreatment LSA score was 67.1. On average, LSA declined 10.1 points from pretreatment to 1 month and remained stable at 6 months. Pretreatment LSA score was associated with several demographic, clinical, geriatric assessment, and symptom characteristics. LSA decline at 1 month was greater among patients with high anxiety (slope = -12.6 vs. -2.3, p = 0.048). Pretreatment body mass index <21 kg/m² was associated with LSA improvement from 1 to 6 months (slope = 4.1 vs. -0.04, p = 0.003). Joint displays illustrated the impact of different life-space trajectories on patients' lives in their words.

Conclusion

Older adults with NSCLC have low pretreatment life space with many developing restricted life space during treatment. Incorporating life-space assessments into clinical cancer care may help older adults concretely visualize how treatment might impact their daily function to allow for informed decision making and identify early changes in mobility to implement supportive interventions.

Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.