Using Real-world Data to Define a Validated Nomogram for Advanced Bladder Cancer Patients Who Respond to Immunotherapy.

AIMS: Immune checkpoint inhibitors (ICIs) are used in incurable urothelial cancers, both in chemo-naïve and platinum-refractory patients. Efficacy and toxicity data published outside controlled clinical trials are limited. We report overall survival, progression-free survival and toxicities of ICIs in locally advanced (LABC) or metastatic bladder cancer (MBC). We aimed to develop and validate a prognostic model for these patients. MATERIALS AND METHODS: A multicentre real-world individual patient-level data study (n = 272) evaluating ICIs in the first-line platinum-ineligible or platinum-refractory setting for LABC/MBC between March 2017 and February 2020 was undertaken. Cox regression analyses evaluated the association of prognostic factors with overall survival. Data were split to create a training (n = 208) and validation (n = 64) cohort. The backward elimination method with a P-value cut-off of 0.05 was used to develop a reduced prognostic model using the training data set. The concordance index and assessment of observed versus predicted survival probabilities were used to evaluate the final model. RESULTS: The median follow-up was 18.9 (15.8-21.5) months. The median overall survival and progression-free survival in the training cohort were 9.2 (95% confidence interval 7.4-10.5) and 4.5 months (3.5-5.7), respectively. The most common grade 1/2 adverse events recorded were fatigue (47.8%) and infection (19.9%). Five key prognostic factors found in the training set were low haemoglobin, high neutrophil count, choice of immunotherapy favouring pembrolizumab, presence of liver metastasis and steroid use within 30 days of treatment. The concordance index for the training and validation cohorts was 0.66 (standard error = 0.05) and 0.64 (standard error = 0.04), respectively, for the final model. A nomogram was developed to calculate the expected survival probabilities based on risk factors. CONCLUSIONS: Real-world data were used to produce a validated prognostic model for overall survival in LABC/MBC treated with ICIs. This model could assist in patient stratification, interpreting and framing future trials incorporating PD-1/PD-L1 inhibitors in LABC/MBC.

Translation of Prognostic and Pharmacodynamic Biomarkers from Trial to Non-trial Patients with Metastatic Castration-resistant Prostate Cancer Treated with Docetaxel.

AIMS: We conducted a pooled analysis of four randomised controlled trials and a non-trial retrospective dataset to study the changes in serum prostate-specific antigen (PSA) concentrations during treatment and its impact on survival in men treated with docetaxel for metastatic castration-resistant prostate cancer. We also compared the outcomes and pre-treatment prognostic factors between trial and non-trial patients. MATERIALS AND METHODS: Data were obtained from four randomised controlled trials and a non-trial cohort from a tertiary cancer centre. The PSA kinetics covariates chosen were absolute value (PSAT), best percentage change (BPCH) and tumour growth rate (K). The association between the covariates collected and overall survival was assessed within a Cox proportional hazards model. How well a covariate captured the difference between trial and non-trial patients was assessed by reporting on models with or without trial status as a covariate. RESULTS: We reviewed individual datasets of 2282 patients. The median overall survival for trial patients was 20.4 (95% confidence interval 19.6-22.2) months and for the non-trial cohort was 12.4 (10.7-14.7) months (P < 0.001). Of the pre-treatment factors, we found that only lactate dehydrogenase fully captured the difference in prognosis between the trial and non-trial cohorts. All PSA kinetic metrics appeared to be prognostic in both the trial and non-trial patients. However, the effect size was reduced in non-trial versus trial patients (interaction P < 0.001). Of the time-dependent covariates, we found that BPCH best captured the difference between trial and non-trial patient prognosis. CONCLUSIONS: The analysis presented here highlights how data from open-source trial databases can be combined with emerging clinical practice databases to assess differences between trial versus non-trial patients for particular treatments. These results highlight the importance of developing prognostic models using both pre-treatment and time-dependent biomarkers of new treatments.

A practical approach to bladder preservation with hypofractionated radiotherapy for localised muscle-invasive bladder cancer.

Bladder preservation with trimodality treatment (TMT) is an alternative strategy to radical cystectomy (RC) for the management of localised muscle invasive bladder cancer (MIBC). TMT comprises of transurethral resection of the bladder tumour (TURBT) followed by radiotherapy with concurrent radiosensitisation. TMT studies have shown neo-adjuvant chemotherapy with cisplatin-based regimens is often given to further improve survival outcomes. A hypofractionated radiotherapy regimen is preferable due to its non-inferiority in local control and late toxicities. Radiosensitisation can comprise concurrent chemotherapy (with gemcitabine, cisplatin or combination fluorouracil and mitomycin), CON (carbogen and nicotinomide) or hyperthermic treatment. Radiotherapy techniques are continuously improving and becoming more personalised. As the bladder is a mobile structure subject to volumetric changes from filling, an adaptive approach can optimise bladder coverage and reduce dose to normal tissue. Adaptive radiotherapy (ART) is an evolving field that aims to overcome this. Improved knowledge of tumour biology and advances in imaging techniques aims to further optimise and personalise treatment.

A systematic review and meta-analysis of cancer patients affected by a novel coronavirus.

BACKGROUND: Cancer patients with COVID-19 disease have been reported to have double the case fatality rate of the general population. MATERIALS AND METHODS: A systematic search of PubMed/MEDLINE, Embase, Cochrane Central, Google Scholar, and MedRxiv was done for studies on cancer patients with COVID-19. Pooled proportions were calculated for categorical variables. Odds ratio and forest plots were constructed for both primary and secondary outcomes. The random-effects model was used to account for heterogeneity between studies. RESULTS: This systematic review of 31 studies and meta-analysis of 181,323 patients from 26 studies involving 23,736 cancer patients is the largest meta-analysis to the best of our knowledge assessing outcomes in cancer patients affected by COVID-19. Our meta-analysis shows that cancer patients with COVID-19 have a higher likelihood of death (odds ratio, OR 2.54), which was largely driven by mortality among patients in China. Cancer patients were more likely to be intubated, although ICU admission rates were not statistically significant. Among cancer subtypes, the mortality was highest in hematological malignancies (OR 2.43) followed by lung cancer (OR 1.8). There was no association between receipt of a particular type of oncologic therapy and mortality. Our study showed that cancer patients affected by COVID-19 are a decade older than the normal population and have a higher proportion of co-morbidities. There was insufficient data to assess the association of COVID-directed therapy and survival outcomes in cancer patients. Despite the heterogeneity of studies and inconsistencies in reported variables and outcomes, these data could guide clinical practice and oncologic care during this unprecedented global health pandemic. CONCLUSION: Cancer patients with COVID-19 disease are at increased risk of mortality and morbidity. A more nuanced understanding of the interaction between cancer-directed therapies and COVID-19-directed therapies is needed. This will require uniform prospective recording of data, possibly in multi-institutional registry databases.