Background During the COVID-19 lockdown, referrals via the 2-week-wait urgent pathway for suspected cancer in England, UK, are reported to have decreased by up to 84%. We aimed to examine the impact of different scenarios of lockdown-accumulated backlog in cancer referrals on cancer survival, and the impact on survival per referred patient due to delayed referral versus risk of death from nosocomial infection with severe acute respiratory syndrome coronavirus 2. Methods In this modelling study, we used age-stratified and stage-stratified 10-year cancer survival estimates for patients in England, UK, for 20 common tumour types diagnosed in 2008–17 at age 30 years and older from Public Health England. We also used data for cancer diagnoses made via the 2-week-wait referral pathway in 2013–16 from the Cancer Waiting Times system from NHS Digital. We applied per-day hazard ratios (HRs) for cancer progression that we generated from observational studies of delay to treatment. We quantified the annual numbers of cancers at stage I–III diagnosed via the 2-week-wait pathway using 2-week-wait age-specific and stage-specific breakdowns. From these numbers, we estimated the aggregate number of lives and life-years lost in England for per-patient delays of 1–6 months in presentation, diagnosis, or cancer treatment, or a combination of these. We assessed three scenarios of a 3-month period of lockdown during which 25%, 50%, and 75% of the normal monthly volumes of symptomatic patients delayed their presentation until after lockdown. Using referral-to-diagnosis conversion rates and COVID-19 case-fatality rates, we also estimated the survival increment per patient referred. Findings Across England in 2013–16, an average of 6281 patients with stage I–III cancer were diagnosed via the 2-week-wait pathway per month, of whom 1691 (27%) would be predicted to die within 10 years from their disease. Delays in presentation via the 2-week-wait pathway over a 3-month lockdown period (with an average presentational delay of 2 months per patient) would result in 181 additional lives and 3316 life-years lost as a result of a backlog of referrals of 25%, 361 additional lives and 6632 life-years lost for a 50% backlog of referrals, and 542 additional lives and 9948 life-years lost for a 75% backlog in referrals. Compared with all diagnostics for the backlog being done in month 1 after lockdown, additional capacity across months 1–3 would result in 90 additional lives and 1662 live-years lost due to diagnostic delays for the 25% backlog scenario, 183 additional lives and 3362 life-years lost under the 50% backlog scenario, and 276 additional lives and 5075 life-years lost under the 75% backlog scenario. However, a delay in additional diagnostic capacity with provision spread across months 3–8 after lockdown would result in 401 additional lives and 7332 life-years lost due to diagnostic delays under the 25% backlog scenario, 811 additional lives and 14 873 life-years l...

NMSC is a greater clinical problem in renal transplant recipients living in subtropical Queensland, Australia, than is shown by currently available registry data. This has implications for the development of prevention and surveillance strategies.

We analysed the expression profiles of 70 kidney tumors of different histological subtypes to determine if these subgroups can be distinguished by their gene expression profiles, and to gain insights into the molecular mechanisms underlying each subtype. In all, 39 clear cell renal cell carcinomas (RCC), seven primary and one metastatic papillary RCC, six granular RCC from old classification, five chromophobe RCC, five sarcomatoid RCC, two oncocytomas, three transitional cell carcinomas (TCC) of the renal pelvis and five Wilms' tumors were compared with noncancerous kidney tissues using microarrays containing 19 968 cDNAs. Based on global gene clustering of 3560 selected cDNAs, we found distinct molecular signatures in clear cell, papillary, chromophobe RCC/ oncocytoma, TCC and Wilms' subtypes. The close clustering in each of these subtypes points to different tumorigenic pathways as reflected by their histological characteristics. In the clear cell RCC clustering, two subgroups emerged that correlated with clinical outcomes, confirming the potential use of gene expression signatures as a predictor of survival. In the so-called granular cell RCC (terminology for a subtype that is no longer preferred), none of the six cases clusters together, supporting the current view that they do not represent a single entity. Blinded histological re-evaluation of four cases of 'granular RCC' led to their reassignment to other existing histological subtypes, each compatible with our molecular classification. Finally, we found gene sets specific to each subtype. In order to establish the use of some of these genes as novel subtype markers, we selected four genes and performed immunohistochemical analysis on 40 cases of primary kidney tumors. The results were consistent with the gene expression microarray data: glutathione S-transferase a was highly expressed in clear cell RCC, a methylacyl racemase in papillary RCC, carbonic anhydrase II in chromophobe RCC and K19 in TCC. In conclusion, we demonstrated that molecular profiles of kidney cancers closely correlated with their histological subtypes. We have also identified in these subtypes differentially expressed genes that could have important diagnostic and therapeutic implications.

The only significant adverse effect of obesity on renal transplant outcomes was an increase in wound complications, which were generally of minor consequence. Provided that adequate care is taken to avoid transplanting patients with significant cardiovascular disease, obese recipients can achieve excellent long-term patient and graft survivals that are on par with their nonobese counterparts. Denying patients access to renal transplantation on the basis of obesity per se does not appear to be justified.