Routine COVID-19 testing may not be necessary for most cancer patients

Cancer patients are at risk for severe complications or death from COVID-19 infection. Therefore, the need for routine COVID-19 testing in this population was evaluated. Between 1st August and 30th October 2020, 150 cancer patients were included. Symptoms of COVID-19 infection were evaluated. All eligible individuals went through RT-PCR and serological tests for COVID-19. At the same time, 920 non-cancer patients were recruited from a random sample of individuals who were subject to routine molecular and anti-body screening tests. Of 150 cancer patients, 7 (4.7%) were RT-PCR positive. Comorbidity made a significant difference in the RT-PCR positivity of cancer patients, 71.4% positive versus 25.8% negative (P-value = 0.02). The average age for negative and positive groups was 53.3 and 58.2 respectively (P-value = 0.01). No significant difference was observed between cancer and non-cancer patients regarding COVID-19 antibody tests. However, cancer patients were 3 times less likely to have a positive RT-PCR test result OR = 0.33 (CI: 0.15–0.73). The probability of cancer patients having a positive routine test was significantly lower than non-cancer patients, and the concept that all cancer patients should be routinely tested for COVID-19 may be incorrect. Nevertheless, there may be a subgroup of patients with comorbidities or older age who may benefit from routine COVID-19 testing. Importantly, these results could not be subjected to multivariate analysis.

DETERMINING PROBABILITY OF CANCER CELL TRANSFOMATION AT HUMAN PAPILLOMAVIRUS INFECTION

Aim. The purpose of the work was to assess the probability of cancerous transformation of cells for viruses of high and low oncogenic risk. Aim. The purpose of the work was to assess the probability of cancerous transformation of cells for viruses of high and low oncogenic risk. Results. Using normalized squared error (NSE) for viruses of high (20 strains) and low (153 strains) oncogenic risk, rank statistic of 2-exponential type was build. For productive papillomavirus infection, NSE function was determined as the growing accurate 2-exponent of a cell layer basal to the epithelial surface. Logarithm of NSE numerical values is proportional to the cell entropy that is connected with the availability of virus DNA. To calculate entropy, generalized Hartley formula was used with the informational cell of dimension d: H = NdLOG(NSE), where N is the generalized cell coordinate. Conclusions. Using a statistical ensemble of E6 proteins separately for viruses of high and low oncogenic risk made it possible to assess the probability of cancerous transformation of cells, which was proportional to the ratio of the area of entropy of cancer transformation to the area of the productive entropy region papillomavirus infection.

How to Predict Cancer-Specific Death of Patients with Chondrosarcoma: A Prognostic Model Based on Competing Risk

Background. As chondrosarcoma is the second highest primary malignant tumor of bone, it is necessary to find a way to predict the prognosis of chondrosarcoma. But the current model rarely involves the study of competing risk. This is a retrospective study with the aim of establishing a prognostic model and a nomogram based on competing risk to predict the probability of cancer-specific death (CSD) at 3 and 5 years. The Fine and Gray regression is a targeted statistical method, which makes the results more authentic and reliable.Methods. A total of 1674 chondrosarcoma patients were identified from the SEER database, and they were divided into training cohort and validation cohort by year of diagnosis. These two cohorts were used to develop and validate the prognostic model to predict the 3-year and 5-year probabilities of CSD, with non-CSD as the competing risk. Model accuracy made use of some verification functions, such as C-index, receiver operating characteristic curve (ROC), calibration plot, area under curve (AUC) and Brier score.Results. According to the outcomes of the model: older age (subdistribution hazards ratio(95%CI): 1.02 (1.01-1.03); P<0.001), dedifferentiated CHS (SHR(95%CI): 2.16 (1.30-3.59); P=0.003), high grade (SHR(95%CI): 2.60 (1.83-3.68); P<0.001), Regional involvement (SHR(95%CI): 3.15 (2.01-4.93); P<0.001), Distant metastasis (SHR(95%CI): 11.56 (6.82-19.59); P<0.001), tumor excision (SHR(95%CI): 0.47 (0.25-0.87); P=0.02) and Radical resection (SHR(95%CI): 0.54 (0.32-0.90); P=0.02) were significantly. They obviously promoted the increase of CSD.Conclusion. This prognostic model considered the competing risks of chondrosarcoma, and the nomogram can effectively predict the probability of CSD in patients with chondrosarcoma, which is suitable for clinical application.

Optimizing the management of patients with small renal masses in a Canadian context: A Markov decision-analysis model

Introduction: The management of patients with a small renal mass (SRM) varies significantly. The objective of this study was to determine which initial management strategy resulted in the greatest quality-adjusted life months (QALM) for an index patient with a SRM. Methods: A Markov decision analysis was used to determine the effect of 1) treating patients with a partial nephrectomy (PN); 2) active surveillance; and 3) renal mass biopsy on QALM over a 10-year horizon. All relevant health states were modelled. Biopsy sensitivity and specificity were modelled assuming an 80% prevalence of cancer using procedural pathology as the gold standard. Health state utilities were obtained from the Tufts Medical Centre Cost-Effective Analysis Registry. Deterministic sensitivity analyses were used to test key assumptions. Results: Over a 10-year time horizon for a 70-year-old male with a 2 cm SRM, the biopsy strategy resulted in 38.07 QALM, whereas treating all patients with PN resulted in 37.69 QALM and active surveillance in 36.25 QALM. The model was most sensitive to the probability that a patient would remain alive at baseline. Biopsy was the preferred strategy when sensitivity was greater than 77%. As the underlying probability of cancer increased, the threshold of renal mass biopsy sensitivity to still favor biopsy increased. Conclusions: Renal mass biopsy is the preferred initial management strategy for an index patient with a SRM to optimize QALM. When the probability of cancer is high, centers should aim for a sensitivity of at least 77% in order to consider a biopsy first strategy.

Molecular alterations in Hürthle cell nodules and preoperative cancer risk

Hürthle cell carcinoma (HCC) is a distinct type of thyroid cancer genetically characterized by DNA copy number alterations (CNA), typically of genome haploidization type (GH-type). However, whether CNA also occurs in benign Hürthle cell adenomas (HCA) or Hürthle cell hyperplastic nodules (HCHN), and have diagnostic impact in fine-needle aspiration (FNA) samples, remains unknown. To address these questions, we (1) analyzed 26 HCC, 24 HCA, and 8 HCHN tissues for CNA and other mutations using ThyroSeq v3 (TSv3) next-generation sequencing panel, and (2) determined cancer rate in 111 FNA samples with CNA and known surgical outcome. We identified CNA, more often of the GH-type, in 81% of HCC and in 38% HCA, but not in HCHN. Among four HCC with distant metastasis, all had CNA and three TERT mutations. Overall, positive TSv3 results were obtained in 24 (92%) HCC, including all with ATA high risk of recurrence or metastasis. Among 111 FNA cases with CNA, 38 (34%) were malignant and 73 (66%) benign. A significant correlation between cancer rate and nodule size was observed, particularly among cases with GH-type CNA, where every additional centimeter of nodule size increased the malignancy odds by 1.9 (95% CI 1.3–2.7; P = 0.001). In summary, the results of this study demonstrate that CNA characteristic of HCC also occur in HCA, although with lower frequency, and probability of cancer in nodules with CNA increases with nodule size. Detection of CNA, in conjunction with other mutations and nodule size, is helpful in predicting malignancy in thyroid nodules.

Impact of Chemotherapy and Radiotherapy on the Survival of Elderly Esophagus Cancer Patients after Surgery: A SEER Database Analysis

BackgroundEsophagus cancer (EC) is a common and lethal carcinoma, however, the effectiveness and feasibility of the conventional treatments for the elderly patients with surgery have not been discussed fully. The purpose of the current study is to discuss the potential effect of chemotherapy and radiotherapy on the prognosis.ResultsBy PSM, chemotherapy (sHR: 0.588, 95%CI: 0.453-0.763, P<0.001) and radiotherapy (sHR: 0.652, 95%CI: 0.513-0.83, P<0.001) were showed a negative correlation to the probability of cancer specific death (CSD). Based on the nomogram, patients with poor differentiation, large tumor size, advanced T-staging, lymphatic metastasis and distant metastasis tended to benefit from chemotherapy (HR: 0.441, 95%CI: 0.364-0.533, P < 0.001) or radiotherapy (HR: 0.539, 95%CI: 0.448-0.649, P < 0.001) to decrease the probabilities of CSD, while no benefit or even harm was showed among the low-risk ones. ConclusionAggressive treatment such as chemotherapy or radiotherapy was considered effective for the selective elder patients with EC.

Temporal order of mutations influences cancer initiation dynamics

Cancer is a set of genetic diseases that are driven by mutations. It was recently discovered that the temporal order of genetic mutations affects the cancer evolution and even the nature of the decease itself. The mechanistic origin of these observations, however, remain not well understood. Here we present a theoretical model for cancer initiation dynamics that allows us to quantify the impact of the temporal order of mutations. In our approach, the cancer initiation process is viewed as a set of stochastic transitions between discrete states defined by the different numbers of mutated cells. Using a first-passage analysis, probabilities and times before the cancer initiation are explicitly evaluated for two alternative sequences of two mutations. It is found that the probability of cancer initiation is determined only by the first mutation, while the dynamics is specified by both mutations. In addition, it is shown that the acquisition of a mutation with higher fitness before mutation with lower fitness increases the probability of the tumor formation but delays the cancer initiation. Theoretical results are explained using effective free-energy landscapes.

Metrics for evaluating polygenic risk scores

There is growing interest in the use of polygenic risk scores based on genetic variants to predict cancer incidence. The type of metric used to evaluate the predictive performance of polygenic risk scores plays a crucial role in their interpretation. I compare three metrics for this evaluation: the area under the Receiver Operating Characteristic curve (AUC), the probability of cancer in a high-risk subset divided by the prevalence of cancer in the population, which I call the subset relative risk (SRR), and the minimum test tradeoff (MTT), which is the minimum number of gene variant ascertainments (one per person) for each correct prediction of cancer to yield a positive expected clinical utility. I show that SRR is a relabeling of AUC. I recommend MTT for the evaluation of polygenic risk scores because, unlike AUC and SRR, it is directly related to the expected clinical utility.