Evaluation of the genetic basis of familial-associated early-onset hematologic cancers in an ancestral/ethnically diverse population.

Genetic predisposition to hematologic malignancies has historically been addressed utilizing patients recruited from clinical trials and pedigrees constructed at major treatment centers. Such efforts leave unexplored the genetic basis of variations in risk by race/ethnic group shown in population-based surveillance data where cancer registration, compulsory by law, delivers universal enrollment. To address this, we performed exome sequencing on DNA isolated from newborn bloodspots derived from sibling pairs with early-onset cancers across California in which at least one of the siblings developed a hematologic cancer, using unbiased recruitment from the full state population. We identified pathogenic/likely pathogenic (P/ LP) variants among 1,172 selected cancer genes that were private or present at low allele frequencies in reference populations. Within 64 subjects from 32 families, we found 9 LP variants shared between siblings, and an additional 7 such variants in singleton children (not shared with their sibling). In 8 of the shared cases, the ancestral origin of the local haplotype that carries P/LP variants matched the dominant global ancestry of study participant families. This was the case for Latino sibling pairs on FLG and CBLB, non-Latino White sibling pairs in TP53 and NOD2, and a shared GATA2 variant for a non-Latino Black sibling pair. A new inherited mutation in HABP2 was identified in a sibling pair, one with diffuse large B-cell lymphoma and the other with neuroblastoma. Overall, the profile of P/LP germline variants across ancestral/ethnic groups suggests that rare alleles contributing to hematologic diseases originate within their race/ethnic origin parental populations, demonstrating the value of this discovery process in diverse, population-based registries.

Analyzing the Correlation Between Surgeon Experience and Patient Length of Hospital Stay.

Introduction  Many clinical, social, and even economic factors have been extensively analyzed in the literature and shown to influence the length of stay (LOS) after spinal procedures. However, surgeon's experience was mostly examined relative to a learning curve and not regarding the time in practice. The primary objective of this study was to determine the effect of one surgeon's experience on the LOS in patients undergoing one- to two-level transforaminal lumbar interbody fusions (TLIFs). Materials and Methods  The study design was a retrospective cohort study of hospital discharge data. The cohort was comprised of 240 consecutive patients who had undergone open one- or two-level elective TLIF procedures for lumbar degenerative disc disease. The primary predictor was the surgeon's experience based upon the years of practice. The primary outcome was LOS, which was controlled by the discharge criteria that remained consistent throughout the study. Results  Based on the Poisson regression model, it can be inferred that the LOS is not significantly associated with a surgeon's experience (Pr(>|t|) = 0.8985, CI: -0.5825 to 0.5114) while controlling for all other variables. Other independent factors did seem to significantly influence patients' LOS, including the admission type (Pr(>|t|) = 9.637-08, CI: -0.8186 to -0.3786), the number of TLIF levels (Pr(>|t|) = 1.721-06, CI: 0.0606 to 0.1446), the Clavien-Dindo ( Pr(>|t|) = 0, CI: 0.1489 to 0.1494), the American Society of Anesthesiologists (ASA) physical status classification scores (Pr(>|t|) = 4.878-3, CI: 0.0336 to 0.1880), and being discharged to skilled nursing facility (Pr(>|t|) = 3.44-2, CI: 0.0127 to 0.3339). Conclusions Based upon the years in practice, surgeon experience was not associated with length of hospitalization and estimated blood loss during surgery in patients undergoing one- and two-level TLIF surgeries. However, while controlling for all other variables, the surgeon's experience and surgical time had a highly significant correlation. The study results clearly demonstrated efficiency, but we did not identify a clear correlation between LOS and surgeon experience overtime suggesting that other factors are likely contributing to such outcome. The average LOS is a complex measure of healthcare resource use and hospital discharge policy or other variables are likely having more effect on LOS than individual surgeons' preferences.