Timing of prognostic discussions in people with advanced cancer: a systematic review.

PURPOSE: Many people with cancer (patients) want to know their prognosis (a quantitative estimate of their life expectancy) but this is often not discussed or poorly communicated. The optimal timing of prognostic discussions with people with advanced cancer is highly personalised and complex. We aimed to find, organise, and summarise research regarding the timing of discussions of prognosis with people with advanced cancer. METHODS: We conducted a systematic review of publications from databases, clinical practice guidelines, and grey literature from inception to 2023. We also searched the reference lists of systematic reviews, editorials, and clinical trial registries. Eligibility criteria included publications regarding adults with advanced cancer that reported a timepoint when a discussion of prognosis occurred or should occur. RESULTS: We included 63 of 798 identified references; most of which were cross-sectional cohort studies with a range of 4-9105 participants. Doctors and patients agreed on several timepoints including at diagnosis of advanced cancer, when the patient asked, upon disease progression, when there were no further anti-cancer treatments, and when recommending palliative care. Most of these timepoints aligned with published guidelines and expert recommendations. Other recommended timepoints depended on the doctor's clinical judgement, such as when the patient 'needed to know' or when the patient 'seemed ready'. CONCLUSIONS: Prognostic discussions with people with advanced cancer need to be individualised, and there are several key timepoints when doctors should attempt to initiate these conversations. These recommended timepoints can inform clinical trial design and communication training for doctors to help improve prognostic understanding.

Accuracy of oncologists' estimates of expected survival time in advanced cancer.

BACKGROUND: To evaluate the claim that oncologists overestimate expected survival time (EST) in advanced cancer. METHODS: We pooled 7 prospective studies in which observed survival time (OST) was compared with EST (median survival in a group of similar patients estimated at baseline by the treating oncologist). We hypothesized that EST would be well calibrated (approximately 50% of EST longer than OST) and imprecise (<30% of EST within 0.67 to 1.33 of OST), and that multiples of EST would provide well-calibrated scenarios for survival time: worst-case (approximately 10% of OST <1/4 of EST), typical (approximately 50% of OST within half to double EST), and best-case (approximately 10% of OST >3 times EST). Associations between baseline characteristics and calibration of EST were assessed. RESULTS: Characteristics of 1,211 patients: median age 66 years, male 61%, primary site lung (40%) and upper gastrointestinal (16%). The median OST was 8 months, and EST was 9 months. Oncologists' estimates of EST were well calibrated (50% longer than OST) and imprecise (28% within 0.67 to 1.33 of OST). Scenarios for survival time based on simple multiples of EST were well calibrated: 8% of patients had an OST less than 1/4 their EST (worst-case), 56% had an OST within half to double their EST (typical), and 11% had an OST greater than 3 times their EST (best-case). Calibration was independent of age, sex, and cancer type. CONCLUSIONS: Oncologists were no more likely to overestimate survival time than to underestimate it. Simple multiples of EST provide well-calibrated estimates of worst-case, typical, and best-case scenarios for survival.

Using three scenarios to explain life expectancy in advanced cancer: attitudes of patients, family members, and other healthcare professionals.

AIM: To evaluate a web-based tool for estimating and explaining three scenarios for expected survival time to people with advanced cancer (patients), their family members (FMs), and other healthcare professionals (HCPs). METHODS: Thirty-three oncologists estimated the "median survival of a group of similar patients" for patients seeking quantitative prognostic information. The web-based tool generated worst-case, most likely, and best-case scenarios for survival based on the oncologist's estimate. Oncologists presented the scenarios to each patient and provided a printed summary to patients, FMs, and HCPs. Attitudes to the information were assessed by questionnaires. Observed survival for each patient was compared with the oncologist's estimated survival and the three scenarios. RESULTS: Prognosis was discussed with 222 patients: median age 67 years; 61% male; most common primary sites pancreas 15%, non-small-cell lung 15%, and colorectal 12%. The median (range) for observed survival times was 9 months (0.5-43) and for oncologist's estimated survival times was 12 months (2-96). Ninety-one percent of patients, 91% of FMs, and 84% of HCPs agreed that it was helpful having life expectancy explained as three scenarios. The majority (77%) of patients judged the information presented about their life expectancy to be the same or better than they had expected before the consultation. The survival estimates met a priori criteria for calibration, precision, and accuracy. CONCLUSIONS: Patients, FMs, and HCPs found it helpful to receive personalized prognostic information formatted as three scenarios for survival. It was feasible, acceptable, and safe to use a web-based resource to do this.

Patient and treatment characteristics of emergency presentations due to immune-mediated toxicities.

BACKGROUND: The prevalence of immune-mediated toxicities from immune checkpoint inhibitors (ICIs) is well described. However, the characteristics and treatment patterns for patients with emergency presentations owing to immune-mediated toxicity are less well known. MATERIALS AND METHODS: This study reviews all emergency presentations in patients treated with ICI at a single centre between May 2018 and March 2020. The aims were to describe and quantify patient and treatment characteristics, toxicity type and outcomes. RESULTS: 1165 patients were treated with ICI, and there were 597 emergency presentations in 370 patients. Of these, 191/597 (32%) were owing to an immune-mediated toxicity, median age was 64 years, and 127/191 (67%) were men. The most common tumour types were melanoma (53%) and lung cancer (22%), and the most common ICI received was ipilimumab + nivolumab combination immunotherapy (42%), followed by pembrolizumab monotherapy (21%) and nivolumab monotherapy (20%). The median number of cycles received was three (range 1-54), and 75/191 (39%) had previous ≥ grade 2 immune-mediated toxicity. 29% patients required second-line immunosuppression. The median time in the hospital was four days. There was a rising number of emergency presentations reflecting overall increasing use of ICI. CONCLUSIONS: Over a quarter of patients treated with ICI had an emergency presentation, and immune-mediated toxicity accounted for 32% of these. A diagnosis of melanoma, treatment with combination immunotherapy and previous ≥ grade 2 immune-mediated toxicity were common in patients with immune-mediated toxicity. These data allow better identification of patients likely to require admission and forward planning for acute oncology services.

SARS-CoV-2 infection and adverse events in patients with cancer receiving immune checkpoint inhibitors: an observational prospective study.

BACKGROUND: In ambulatory patients with cancer with asymptomatic or pauci-symptomatic SARS-CoV-2 infection, the safety of targeted therapies (TTs), chemotherapy (CT) or immune checkpoint inhibitors (ICIs) therapy is still unknown. MATERIAL AND METHODS: From the start of the first epidemic wave of SARS-CoV-2 in Bergamo, Italy, we have prospectively screened all consecutive outpatients who presented for treatment to the Oncology Division of the Papa Giovanni XXIII Hospital, Bergamo for SARS-CoV-2 antigen expression. We identified patients treated with ICIs and compared these to patients with the same cancer subtypes treated with TTs or CT. RESULTS: Between March 5 and May 18, 293 consecutive patients (49% melanoma, 34% non-small cell lung cancer, 9% renal cell carcinoma, 8% other) were included in this study: 159 (54%), 50 (17%) and 84 (29%) received ICIs, CT or TTs, respectively. Overall 89 patients (30.0%) were SARS-CoV-2 positive. Mortality of SARS-CoV-2-positive patients was statistically significantly higher compared with SARS-CoV-2 negative patients (8/89 vs 3/204, respectively, Fisher's exact test p=0.004). All deaths were due to COVID-19. Serious adverse events (SAEs) were more frequent in SARS-CoV-2-positive patients compared with SARS-CoV-2-negative cases (Cochran-Mantel-Haenszel (CMH) test p=0.0008). The incidence of SAEs in SARS-CoV-2 positive compared with SARS-CoV-2 negative patients was similar in ICI and CT patients (17.3% and 3.7% for positive and negative patients in ICIs and 15.4% and 2.7% in CT, Breslow-Day test p=0.891). No COVID-19-related SAEs were observed in the TTs patients. CONCLUSIONS: The incidence of SAEs was higher for SARS-CoV-2-positive patients treated with ICIs and CT, mostly in advanced disease. No SAEs were observed in patients treated with TTs. SAEs were COVID-19 related rather than treatment related. Treatment with ICIs does not appear to significantly increase risk of SAEs compared with CT. This information should be considered when determining treatment options for patients.

Clinical impact of COVID-19 on patients with cancer treated with immune checkpoint inhibition.

BACKGROUND: Patients with cancer who are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are more likely to develop severe illness and die compared with those without cancer. The impact of immune checkpoint inhibition (ICI) on the severity of COVID-19 illness is unknown. The aim of this study was to investigate whether ICI confers an additional risk for severe COVID-19 in patients with cancer. METHODS: We analyzed data from 110 patients with laboratory-confirmed SARS-CoV-2 while on treatment with ICI without chemotherapy in 19 hospitals in North America, Europe and Australia. The primary objective was to describe the clinical course and to identify factors associated with hospital and intensive care (ICU) admission and mortality. FINDINGS: Thirty-five (32%) patients were admitted to hospital and 18 (16%) died. All patients who died had advanced cancer, and only four were admitted to ICU. COVID-19 was the primary cause of death in 8 (7%) patients. Factors independently associated with an increased risk for hospital admission were ECOG ≥2 (OR 39.25, 95% CI 4.17 to 369.2, p=0.0013), treatment with combination ICI (OR 5.68, 95% CI 1.58 to 20.36, p=0.0273) and presence of COVID-19 symptoms (OR 5.30, 95% CI 1.57 to 17.89, p=0.0073). Seventy-six (73%) patients interrupted ICI due to SARS-CoV-2 infection, 43 (57%) of whom had resumed at data cut-off. INTERPRETATION: COVID-19-related mortality in the ICI-treated population does not appear to be higher than previously published mortality rates for patients with cancer. Inpatient mortality of patients with cancer treated with ICI was high in comparison with previously reported rates for hospitalized patients with cancer and was due to COVID-19 in almost half of the cases. We identified factors associated with adverse outcomes in ICI-treated patients with COVID-19.

Factors associated with fear of cancer recurrence in breast and colorectal cancer survivors: A cross-sectional study of cancer survivors.

AIM: To define the prevalence and severity of fear of cancer recurrence and identify factors associated with fear of cancer recurrence in breast cancer and colorectal cancer survivors attending the Sydney Cancer Survivorship Clinic. METHODS: A cross-sectional study was performed using prospectively collected data. Survivors completed questionnaires assessing quality of life (Functional Assessment of Cancer Therapy-General and symptoms (Distress Thermometer, Patient's Disease and Treatment Assessment Form)). Survivors were assessed by a clinical psychologist for the presence of fear of cancer recurrence. Clinical and quality of life variables were evaluated for associations with fear of cancer recurrence. RESULTS: Overall, 315 survivors (181 breast cancer, 134 colorectal cancer) were included. In total, 201 survivors (64%) had fear of cancer recurrence according to psychology assessment, and of the 118 that had fear of cancer recurrence severity recorded, 64 (54%) were rated as moderate-severe. On univariate analysis, fear of cancer recurrence was associated with younger age (P < 0.001), higher distress thermometer score (P = 0.001) and poorer overall wellbeing (P < 0.001). On multivariate analysis, younger age (P = 0.043), being bothered by side effects of treatment (P = 0.023), feeling sad (P = 0.020) and greater worry that their condition will get worse (P = 0.017) were independently associated with fear of cancer recurrence. CONCLUSIONS: Fear of cancer recurrence is common in breast and colorectal cancer survivors, and moderate-severe in over half. Fear of cancer recurrence was independently associated with younger age, feeling sad, being more bothered by side effects.

How long is too long? A scoping review of health system delays in lung cancer.

Earlier access to lung cancer specialist (LCS) care improves survival, highlighting the need for streamlined patient referral. International guidelines recommend 14-day maximum time intervals from general practitioner (GP) referral to first LCS appointment ("GP-LCS interval"), and diagnosis to treatment ("treatment interval"). We compared time intervals in lung cancer care against timeframe benchmarks, and explored barriers and facilitators to timely care.We conducted a scoping review of literature from MEDLINE, Embase, Scopus and hand searches. Primary end-points were GP-LCS and treatment intervals. Performance against guidelines and factors responsible for delays were explored. We used descriptive statistics and nonparametric Wilcoxon rank sum tests to compare intervals in studies reporting fast-track interventions.Of 1343 identified studies, 128 full-text articles were eligible. Only 33 (26%) studies reported GP-LCS intervals, with an overall median of 7 days and distributions largely meeting guidelines. Overall, 52 (41%) studies reported treatment intervals, with a median of 27 days, and distributions of times falling short of guidelines. There was no effect of fast-track interventions on reducing time intervals. Lack of symptoms and multiple procedures or specialist visits were suggested causes for delay.Although most patients with lung cancer see a specialist within a reasonable timeframe, treatment commencement is often delayed. There is regional variation in establishing timeliness of care.