Theranostics in prostate cancer

177Lu-PSMA is a novel therapy in patients with metastatic castration-resistant prostate carcinoma (mCRPC). The radiolabeled drug is administered intravenously, usually in 4–6 cycles, in which β‑radiation induces intracellular DNA damage and cell death of PSMA-expressing prostate cancer cells. The γ‑decay of the radionuclide can be used for imaging and dosimetry. An international phase III study showed that end stage mCRPC patients that received 177Lu-PSMA had a survival benefit (15.3 vs. 11.3 months; p &lt; 0.001). Moreover, several studies suggest that ~25% of these heavily pre-treated patients respond better and likely have a longer survival benefit. The most important side effects are: grade I–II fatigue (~40%) and xerostomia (~40%), which are mostly transient. Grade III–IV CTCAE hematologic toxicity (thrombocytopenia, leukopenia) was seen in ~8% of patients. Recently, the American Food and Drug Administration (FDA) and the European Medicines Agency (EMA) approved the drug for patients with end stage prostate cancer. Currently, there are several studies investigating if patients in an earlier stage of the disease, metastatic hormone-sensitive or hormone-naïf, can also benefit from therapy with 177Lu-PSMA.</p

Theranostics in prostate cancer

177Lu-PSMA is a novel therapy in patients with metastatic castration-resistant prostate carcinoma (mCRPC). The radiolabeled drug is administered intravenously, usually in 4–6 cycles, in which β‑radiation induces intracellular DNA damage and cell death of PSMA-expressing prostate cancer cells. The γ‑decay of the radionuclide can be used for imaging and dosimetry. An international phase III study showed that end stage mCRPC patients that received 177Lu-PSMA had a survival benefit (15.3 vs. 11.3 months; p &lt; 0.001). Moreover, several studies suggest that ~25% of these heavily pre-treated patients respond better and likely have a longer survival benefit. The most important side effects are: grade I–II fatigue (~40%) and xerostomia (~40%), which are mostly transient. Grade III–IV CTCAE hematologic toxicity (thrombocytopenia, leukopenia) was seen in ~8% of patients. Recently, the American Food and Drug Administration (FDA) and the European Medicines Agency (EMA) approved the drug for patients with end stage prostate cancer. Currently, there are several studies investigating if patients in an earlier stage of the disease, metastatic hormone-sensitive or hormone-naïf, can also benefit from therapy with 177Lu-PSMA.</p

Evaluation of the performance of algorithms mapping EORTC QLQ-C30 onto the EQ-5D index in a metastatic colorectal cancer cost-effectiveness model

BACKGROUND: Cost-effectiveness models require quality of life utilities calculated from generic preference-based questionnaires, such as EQ-5D. We evaluated the performance of available algorithms for QLQ-C30 conversion into EQ-5D-3L based ut

An exceptional venous pattern in a patient with cancer

A 71-year-old female was treated with carboplatin and paclitaxel for an endometrial carcinosarcoma. The patient demonstrated an unusual type 1 allergic reaction on carboplatin, which started with an erythematous urticarial venous pattern proximal from the venous catheter with carboplatin

Comparing Strategies for Modeling Competing Risks in Discrete-Event Simulations : A Simulation Study and Illustration in Colorectal Cancer

Background. Different strategies toward implementing competing risks in discrete-event simulation (DES) models are available. This study aims to provide recommendations regarding modeling approaches that can be defined based on these strategies by performing a quantitative comparison of alternative modeling approaches. Methods. Four modeling approaches were defined: 1) event-specific distribution (ESD), 2) event-specific probability and distribution (ESPD), 3) unimodal joint distribution and regression model (UDR), and 4) multimodal joint distribution and regression model (MDR). Each modeling approach was applied to uncensored individual patient data in a simulation study and a case study in colorectal cancer. Their performance was assessed in terms of relative event incidence difference, relative absolute event incidence difference, and relative entropy of time-to-event distributions. Differences in health economic outcomes were also illustrated for the case study. Results. In the simulation study, the ESPD and MDR approaches outperformed the ESD and UDR approaches, in terms of both event incidence differences and relative entropy. Disease pathway and data characteristics, such as the number of competing risks and overlap between competing time-to-event distributions, substantially affected the approaches’ performance. Although no considerable differences in health economic outcomes were observed, the case study showed that the ESPD approach was most sensitive to low event rates, which negatively affected performance. Conclusions. Based on overall performance, the recommended modeling approach for implementing competing risks in DES models is the MDR approach, which is defined according to the general strategy of selecting the time-to-event first and the corresponding event second. The ESPD approach is a less complex and equally performing alternative if sufficient observations are available for each competing event (i.e., the internal validity shows appropriate data representation)

The etiology and outcome of non-traumatic coma in critical care: a systematic review

BACKGROUND: Non-traumatic coma (NTC) is a serious condition requiring swift medical or surgical decision making upon arrival at the emergency department. Knowledge of the most frequent etiologies of NTC and associated mortality might improve the management of these patients. Here, we present the results of a systematic literature search on the etiologies and prognosis of NTC. METHODS: Two reviewers independently performed a systematic literature search in the Pubmed, Embase and Cochrane databases with subsequent reference and citation checking. Inclusion criteria were retrospective or prospective observational studies on NTC, which reported on etiologies and prognostic information of patients admitted to the emergency department or intensive care unit. RESULTS: Eventually, 14 studies with enough data on NTC, were selected for this systematic literature review. The most common causes of NTC were stroke (6-54%), post-anoxic coma (3-42%), poisoning (<1-39%) and metabolic causes (1-29%). NTC was also often caused by infections, especially in African studies affecting 10-51% of patients. The NTC mortality rate ranged from 25 to 87% and the mortality rate continued to increase long after the event had occurred. Also, 5-25% of patients remained moderately-severely disabled or in permanent vegetative state. The mortality was highest for stroke (60-95%) and post-anoxic coma (54-89%) and lowest for poisoning (0-39%) and epilepsy (0-10%). CONCLUSION: NTC represents a challenge to the emergency and the critical care physicians with an important mortality and moderate-severe disability rate. Even though, included studies were very heterogeneous, the most common causes of NTC are stroke, post anoxic, poisoning and various metabolic etiologies. The best outcome is achieved for patients with poisoning and epilepsy, while the worst outcome was seen in patients with stroke and post-anoxic coma. Adequate knowledge of the most common causes of NTC and prioritizing the causes by mortality ensures a swift and adequate work-up in diagnosis of NTC and may improve outcome

Comparing Modeling Approaches for Discrete Event Simulations With Competing Risks Based on Censored Individual Patient Data: A Simulation Study and Illustration in Colorectal Cancer

Objectives: This study aimed to provide detailed guidance on modeling approaches for implementing competing events in discrete event simulations based on censored individual patient data (IPD). Methods: The event-specific distributions (ESDs) approach sampled times from event-specific time-to-event distributions and simulated the first event to occur. The unimodal distribution and regression approach sampled a time from a combined unimodal time-to-event distribution, representing all events, and used a (multinomial) logistic regression model to select the event to be simulated. A simulation study assessed performance in terms of relative absolute event incidence difference and relative entropy of time-to-event distributions for different types and levels of right censoring, numbers of events, distribution overlap, and sample sizes. Differences in cost-effectiveness estimates were illustrated in a colorectal cancer case study. Results: Increased levels of censoring negatively affected the modeling approaches’ performance. A lower number of competing events and higher overlap of distributions improved performance. When IPD were censored at random times, ESD performed best. When censoring occurred owing to a maximum follow-up time for 2 events, ESD performed better for a low level of censoring (ie, 10%). For 3 or 4 competing events, ESD better represented the probabilities of events, whereas unimodal distribution and regression better represented the time to events. Differences in cost-effectiveness estimates, both compared with no censoring and between approaches, increased with increasing censoring levels. Conclusions: Modelers should be aware of the different modeling approaches available and that selection between approaches may be informed by data characteristics. Performing and reporting extensive validation efforts remains essential to ensure IPD are appropriately represented

Matching the model with the evidence : comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients

Background: Individual patient data, e.g. from clinical trials, often need to be extrapolated or combined with additional evidence when assessing long-term impact in cost-effectiveness modeling studies. Different modeling methods can be used to represent the complex dynamics of clinical practice; the choice of which may impact cost-effectiveness outcomes. We compare the use of a previously designed cohort discrete-time state-transition model (DT-STM) with a discrete event simulation (DES) model. Methods: The original DT-STM was replicated and a DES model developed using AnyLogic software. Models were populated using individual patient data of a phase III study in metastatic colorectal cancer patients, and compared based on their evidence structure, internal validity, and cost-effectiveness outcomes. The DT-STM used time-dependent transition probabilities, whereas the DES model was populated using parametric distributions. Results: The estimated time-dependent transition probabilities for the DT-STM were irregular and more sensitive to single events due to the required small cycle length and limited number of event observations, whereas parametric distributions resulted in smooth time-to-event curves for the DES model. Although the DT-STM and DES model both yielded similar time-to-event curves, the DES model represented the trial data more accurately in terms of mean health-state durations. The incremental cost-effectiveness ratio (ICER) was €172,443 and €168,383 per Quality Adjusted Life Year gained for the DT-STM and DES model, respectively. Conclusion: DES represents time-to-event data from clinical trials more naturally and accurately than DT-STM when few events are observed per time cycle. As a consequence, DES is expected to yield a more accurate ICER

The etiology and outcome of non-traumatic coma in critical care: a systematic review

BACKGROUND: Non-traumatic coma (NTC) is a serious condition requiring swift medical or surgical decision making upon arrival at the emergency department. Knowledge of the most frequent etiologies of NTC and associated mortality might improve the management of these patients. Here, we present the results of a systematic literature search on the etiologies and prognosis of NTC. METHODS: Two reviewers independently performed a systematic literature search in the Pubmed, Embase and Cochrane databases with subsequent reference and citation checking. Inclusion criteria were retrospective or prospective observational studies on NTC, which reported on etiologies and prognostic information of patients admitted to the emergency department or intensive care unit. RESULTS: Eventually, 14 studies with enough data on NTC, were selected for this systematic literature review. The most common causes of NTC were stroke (6-54%), post-anoxic coma (3-42%), poisoning (<1-39%) and metabolic causes (1-29%). NTC was also often caused by infections, especially in African studies affecting 10-51% of patients. The NTC mortality rate ranged from 25 to 87% and the mortality rate continued to increase long after the event had occurred. Also, 5-25% of patients remained moderately-severely disabled or in permanent vegetative state. The mortality was highest for stroke (60-95%) and post-anoxic coma (54-89%) and lowest for poisoning (0-39%) and epilepsy (0-10%). CONCLUSION: NTC represents a challenge to the emergency and the critical care physicians with an important mortality and moderate-severe disability rate. Even though, included studies were very heterogeneous, the most common causes of NTC are stroke, post anoxic, poisoning and various metabolic etiologies. The best outcome is achieved for patients with poisoning and epilepsy, while the worst outcome was seen in patients with stroke and post-anoxic coma. Adequate knowledge of the most common causes of NTC and prioritizing the causes by mortality ensures a swift and adequate work-up in diagnosis of NTC and may improve outcome