Factors Associated With Prescription of Systemic Therapy in Real-world Patients With Metastatic Renal Cell Cancer Managed in a Rural Region.

Background/Aim: Numerous new treatment options have been approved for metastatic renal cell carcinoma (mRCC) in the last decade. Nevertheless, not all patients receive systemic therapy. Certain patients present with very advanced disease, poor Eastern Cooperative Oncology Group performance status (ECOG PS), or severe comorbidity, i.e. factors that lead oncologists to prefer best supportive care (BSC) instead of systemic therapy. The aim of this quality-of-care study was to identify baseline factors (disparities) associated with receipt of systemic therapy rather than BSC. Patients and Methods: This retrospective analysis included 140 consecutive patients managed in a rural region of Norway (2007-2022). Two differently managed groups were compared in univariate tests followed by multi-nominal regression. Results: The majority of patients (n=95, 68%) had received systemic therapy. Typical patients were males in their 60s or 70s, with clear cell histology, prior nephrectomy, and intermediate prognostic features. Patients who received systemic therapy lived significantly longer than those who did not (median 30.4 versus 5.0 months, p<0.001). Survival benefit of systemic treatment was observed even in patients with ECOG PS3 or age ≥80 years. In addition to younger age (p<0.001) and better ECOG PS (p<0.001), metachronous presentation was associated with higher rates of systemic therapy utilization (p=0.03). Conclusion: Assignment to systemic therapy for mRCC was individualized in the present patient population. In all age and ECOG PS subgroups, systemic therapy was associated with better survival (doubling at least). Optimum utilization rates are difficult to determine. However, in light of the survival outcomes, a rate of 12% in patients aged 80 years or older appears rather low.

Sex Differences in Presentation, Treatment, and Survival in Patients Receiving Palliative (Chemo)Radiotherapy for Non-Small Cell Lung Cancer.

BACKGROUND/AIM: The aim of this study was to analyze sex differences in a real-world cohort of patients who received palliative thoracic radiotherapy or chemoradiotherapy for non-small cell lung cancer. PATIENTS AND METHODS: Retrospectively, baseline, treatment, toxicity, and survival data from a single institution were analyzed. The study included 181 patients (82 females, 99 males). RESULTS: Despite borderline significant differences in disease presentation (T and N stage), final assignment to stage II, III or IV was similar. The same was true for target volume size. Neither radiotherapy parameters nor systemic treatment approaches were significantly different. Toxicity profiles and survival were similar too. Less than 1 out of 3 patients experienced high-grade toxicity, largely esophagitis. Median survival was 8.1 (males) versus 7.8 months (females) and the corresponding 2-year survival rates were 16 and 15%, respectively (p=0.78). CONCLUSION: Relevant sex differences were not observed in this study of common radiotherapy regimes such as 10 fractions of 3 Gy or 15 fractions of 2.8 Gy, the latter often combined with carboplatin/vinorelbine chemotherapy.

Days at home in the last three months of life: patterns-of-care analysis in patients with non-small cell lung cancer.

Introduction: To calculate the number of days patients with terminal non-small cell lung cancer (NSCLC) spent at home in the last 3 months of life, and to identify factors that predict a lower proportion of days at home. Material and methods: Retrospective study of 434 deceased patients with NSCLC. The number of days spent in a hospital or nursing home was identified from electronic health records. Results: Most patients received primary chemotherapy. Only 45% received palliative care provided by a dedicated palliative care team (PCT). In the last 3 months of life, only 39 patients (9%) were not hospitalized. The median number of days spent in hospital was 17, range 0-61. Hospital death occurred in 48%. Admission to a nursing home was recorded in 45%. Overall, the patients spent a median of 64 days at home. Both, older patients and females spent fewer days at home. Family network and aspects of palliative care, possibly reflecting the symptom duration or burden, also impacted days at home. Conclusions: Long-lasting need for PCT support (not just the final 3 months) and earlier necessity for opioid analgesics were predictive for a reduced number of days at home. However, modifiable factors such as sex were identified too.

30-day mortality in patients treated for brain metastases: extracranial causes dominate.

BACKGROUND: Established prognostic models, such as the diagnosis-specific graded prognostic assessment, were not designed to specifically address very short survival. Therefore, a brain metastases-specific 30-day mortality model may be relevant. We hypothesized that in-depth evaluation of a carefully defined cohort with short survival, arbitrarily defined as a maximum of 3 months, may provide signals and insights, which facilitate the development of a 30-day mortality model. METHODS: Retrospective analysis (2011-2021) of patients treated for brain metastases with different approaches. Risk factors for 30-day mortality from radiosurgery or other primary treatment were evaluated. RESULTS: The cause of death was unrelated to brain metastases in 61%. Treatment-related death (grade 5 toxicity) did not occur. Completely unexpected death was not observed, e.g. accident, suicide or sudden cardiac death. Logistic regression analysis showed 9 factors associated with 30-day mortality (each assigned 3-6 points) and a point sum was calculated for each patient. The point sum ranged from 0 (no risk factors for death within 30 days present) to 30. The results can be grouped into 3 or 4 risk categories. Eighty-three percent of patients in the highest risk group (> 16 points) died within 30 days, and none survived for more than 2 months. However, many cases of 30-day mortality (more than half) occurred in intermediate risk categories. CONCLUSION: Extracranial tumor progression was the prevailing cause of 30-day mortality and few, if any deaths could be considered relatively unexpected when looking at the complete oncological picture. We were able to develop a multifactorial prediction model. However, the model's performance was not fully satisfactory and it is not routinely applicable at this point in time, because external validation is needed to confirm our hypothesis-generating findings.

Adverse events in deceased hospitalised cancer patients as a measure of quality and safety in end-of-life cancer care.

BACKGROUND: Anticancer treatment exposes patients to negative consequences such as increased toxicity and decreased quality of life, and there are clear guidelines recommending limiting use of aggressive anticancer treatments for patients near end of life. The aim of this study is to investigate the association between anticancer treatment given during the last 30 days of life and adverse events contributing to death and elucidate how adverse events can be used as a measure of quality and safety in end-of-life cancer care. METHODS: Retrospective cohort study of 247 deceased hospitalised cancer patients at three hospitals in Norway in 2012 and 2013. The Global Trigger Tool method were used to identify adverse events. We used Poisson regression and binary logistic regression to compare adverse events and association with use of anticancer treatment given during the last 30 days of life. RESULTS: 30% of deceased hospitalised cancer patients received some kind of anticancer treatment during the last 30 days of life, mainly systemic anticancer treatment. These patients had 62% more adverse events compared to patients not being treated last 30 days, 39 vs. 24 adverse events per 1000 patient days (p < 0.001, OR 1.62 (1.23-2.15). They also had twice the odds of an adverse event contributing to death compared to patients without such treatment, 33 vs. 18% (p = 0.045, OR 1.85 (1.01-3.36)). Receiving follow up by specialist palliative care reduced the rate of AEs per 1000 patient days in both groups by 29% (p = 0.02, IRR 0.71, CI 95% 0.53-0.96). CONCLUSIONS: Anticancer treatment given during the last 30 days of life is associated with a significantly increased rate of adverse events and related mortality. Patients receiving specialist palliative care had significantly fewer adverse events, supporting recommendations of early integration of palliative care in a patient safety perspective.

Contribution of adverse events to death of hospitalised patients.

Background: There is no standardised method to investigate death as a patient safety indicator and we need valid and reliable measurements to use adverse events contributing to death as a quality measure. Objective: To investigate the contribution of severe adverse events to death in hospitalised patients and clarify methodological differences using the Global Trigger Tool method on all inpatient deaths compared with a sample of general hospitalised patients. Method: Retrospective records reviewing using the Global Trigger Tool method. Results: In 0.3% of hospital admissions, adverse events contribute to inpatient death. Patients who die in hospital have twice the rate of adverse events per 1000 patient days compared with general patients, 76.7 vs 36.5 (p<0.001, RR 2.10, 95% CI 1.79 to 2.47). Patients dying in hospital experience seven times the rate of severe adverse events, 38.4% vs 5.2% (p<0.001, RR 2.10, 95% CI 1.79 to 2.47). For 86 out of 377 inpatient deaths, the adverse event is so severe that it contributes to death. 27.9% of severe adverse events contributing to death originate in primary care. Lower respiratory infections (p<0.001, RR 2.81, 95% CI 1.76 to 4.51), medication harm (p<0.001, RR 5.21, 95% CI 3.04 to 8.94) and pressure ulcers (p=0.04, RR 2.23, 95% CI 1.03 to 4.85) are significantly more frequent for inpatient deaths than in the general sample of hospital patients. Conclusions: Patients dying in hospitals experience seven times the rate of severe adverse events. Reviewing all inpatient death by the Global Trigger Tool method discloses new valid and reliable data of severe adverse events contributing to death which otherwise would be undetected.

Adverse events in hospitalised cancer patients: a comparison to a general hospital population.

BACKGROUND: Patients with cancer are often treated by many healthcare providers, receive complex and potentially toxic treatments that can increase the risk for iatrogenic harm. The aim of this study is to investigate whether hospitalised cancer patients are at higher risk of adverse events (AEs) compared to a general hospital population. MATERIAL AND METHODS: A total of 6720 patient records were retrospectively reviewed comparing AEs in hospitalised cancer patients to a general hospital population in Norway, using the IHI Global Trigger Tool method. RESULTS: 24.2 percent of admissions for cancer patients had an AE compared to 17.4% of admissions of other patients (p < .001, rr 1.39, 95% CI 1.19-1.62). However, cancer patients did not have a higher rate of AEs per 1000 patient days compared to other patients, 37.1 vs. 36.0 (p = .65, rr 0.94, 95% CI 0.90-1.18). No particular cancer category is at higher risk. The rate of AEs increases by 1.05 times for each day spent in hospital. For every year increase in age, the risk for AEs increases by 1.3%. Cancer patients more often have hospital-acquired infections, other surgical complications and AEs related to medications. CONCLUSIONS: Because of higher age, longer length of stay and surgical treatment, hospitalised cancer patients experience AEs more often than other patients.