This Patient Page explains tumor lysis syndrome, how it affects the body, who is at greatest risk, how to recognize it, and measures to help prevent it or treat

Background. Very late recurrence (LR), i.e., >5 years after initial presentation, occurs in about 1% of patients with germ cell tumors of the testis (TGCT) and is associated with poor prognosis. Methods. We retrospectively reviewed the records of patients at the M. D. Anderson Cancer Center who developed LR > 5 years after their initial diagnosis of TGCT. Results. We identified 25 patients who developed LR between July 2007 and August 2020. The median age at the time of LR was 46 years (range, 29–61). Pathology of LR: somatic transformation to carcinoma or sarcoma—11, nonseminoma with yolk sac tumor or teratoma—11, nonseminoma without yolk sac tumor or teratoma—2, not available—1. With a median follow-up of 3.5 years, 68% of patients are alive 3 years after LR. Patients with prior post-chemotherapy consolidation surgery do not have statistically significant longer survival compared to patients who did not receive post-chemotherapy consolidation surgery, 83.3% vs. 60.8% at 3 years, respectively, p = 0.50. Conclusions. Patients with LR > 5 years tend to harbor nonseminoma (with yolk sac tumor and or teratoma). Among these patients, a majority who did not undergo surgery to remove residual disease after chemotherapy developed somatic transformation and succumbed to their LR.

Recently, we demonstrated in female mice that protection against ANG II-induced hypertension and associated cardiovascular changes depend on cytochrome P-450 (CYP)1B1. The present study was conducted to determine if Cyp1b1 gene disruption ameliorates renal dysfunction and organ damage associated with ANG II-induced hypertension in female mice. ANG II (700 ng·kg⁻¹·min⁻¹) infused by miniosmotic pumps for 2 wk in female Cyp1b1^+/+mice did not alter water consumption, urine output, Na⁺excretion, osmolality, or protein excretion. However, in Cyp1b1^−/−mice, ANG II infusion significantly increased ( P < 0.05) water intake (5.50 ± 0.42 ml/24 h with vehicle vs. 8.80 ± 0.60 ml/24 h with ANG II), urine output (1.44 ± 0.37 ml/24 h with vehicle vs. 4.30 ± 0.37 ml/24 h with ANG II), and urinary Na⁺excretion (0.031 ± 0.016 mmol/24 h with vehicle vs. 0.099 ± 0.010 mmol/24 h with ANG II), decreased osmolality (2,630 ± 79 mosM/kg with vehicle vs. 1,280 ± 205 mosM/kg with ANG II), and caused proteinuria (2.60 ± 0.30 mg/24 h with vehicle vs. 6.96 ± 0.55 mg/24 h with ANG II). Infusion of ANG II caused renal fibrosis, as indicated by an accumulation of renal interstitial α-smooth muscle actin, collagen, and transforming growth factor-β in Cyp1b1^−/−but not Cyp1b1^+/+mice. ANG II also increased renal production of ROS and urinary excretion of thiobarburic acid-reactive substances and reduced the activity of antioxidants and urinary excretion of nitrite/nitrate and the 17β-estradiol metabolite 2-methoxyestradiol in Cyp1b1^−/−but not Cyp1b1^+/+mice. These data suggest that Cyp1b1 plays a critical role in female mice in protecting against renal dysfunction and end-organ damage associated with ANG II-induced hypertension, in preventing oxidative stress, and in increasing activity of antioxidant systems, most likely via generation of 2-methoxyestradiol from 17β-estradiol.

The capture of high‐quality treatment data and outcomes is necessary in order to learn from our clinical experiences with big data analytics. In radiotherapy, there are several practical challenges to overcome. Practical aspects of data collection are discussed pointing to a need for a culture change in clinical practice to one that captures structured patient‐related data in routine care in a prospective manner. Radiation dosimetry and the contoured anatomy must also be captured routinely to represent the best estimate of delivered radiation. The quality and integrity present in the data are critical which poses opportunities to introduce electronic validity checking to improve them. Similarly, data completeness and methods and technology to improve the efficiency and sufficiency of data capture can be introduced. In the manuscript, the types of clinical data are discussed including patient reports, images, biospecimens, treatments, and symptom management. With a data‐driven culture, the realization of a learning health system is possible unlocking the potential of big data and its influence on clinical decision‐making and hypothesis generation.