Prognostic factors in advanced cancer patients: evidence-based clinical recommendations--a study by the Steering Committee of the European Association for Palliative Care

Prognostication As an Interactionally Delicate Matter: A Conversation Analytic Study of Hospice Multidisciplinary Team Meetings

Prognostication has been found to be a delicate matter in interactions between palliative care professionals and patients. Studies have investigated how these discussions are managed and how speakers orient to their delicate nature. However, the degree to which prognostication is a delicate matter in discussions between palliative care professionals themselves has yet to be investigated. This study explored how hospice multidisciplinary team (MDT) members oriented to the delicacy of prognostication during their meetings. Video-recordings of 24 hospice MDT meetings were transcribed and analyzed using Conversation Analysis. In-depth analysis of the interactions showed how prognostic discussions were oriented to as delicate. This was displayed through markers such as pauses and self-repair organization including cutting off words and restarts, and through accounts accompanying the prognosis. In this way, it was seen that prognostication was not necessarily straightforward. This was further evidenced when prognostic requests were problematic to respond to. It is noteworthy that prognostic discussions are delicate during hospice MDT meetings. Potential reasons may reach further than the taboo of death and lie within prognostic uncertainty and accountability. Research is warranted to explore what causes this delicacy and whether specific support is needed for hospice staff.

From Pixels to Prognosis: A Survey on AI-Driven Cancer Patient Survival Prediction Using Digital Histology Images

Survival analysis is an integral part of medical statistics that is extensively utilized to establish prognostic indices for mortality or disease recurrence, assess treatment efficacy, and tailor effective treatment plans. The identification of prognostic biomarkers capable of predicting patient survival is a primary objective in the field of cancer research. With the recent integration of digital histology images into routine clinical practice, a plethora of Artificial Intelligence (AI)-based methods for digital pathology has emerged in scholarly literature, facilitating patient survival prediction. These methods have demonstrated remarkable proficiency in analyzing and interpreting whole slide images, yielding results comparable to those of expert pathologists. The complexity of AI-driven techniques is magnified by the distinctive characteristics of digital histology images, including their gigapixel size and diverse tissue appearances. Consequently, advanced patch-based methods are employed to effectively extract features that correlate with patient survival. These computational methods significantly enhance survival prediction accuracy and augment prognostic capabilities in cancer patients. The review discusses the methodologies employed in the literature, their performance metrics, ongoing challenges, and potential solutions for future advancements. This paper explains survival analysis and feature extraction methods for analyzing cancer patients. It also compiles essential acronyms related to cancer precision medicine. Furthermore, it is noteworthy that this is the inaugural review paper in the field. The target audience for this interdisciplinary review comprises AI practitioners, medical statisticians, and progressive oncologists who are enthusiastic about translating AI-driven solutions into clinical practice. We expect this comprehensive review article to guide future research directions in the field of cancer research.

Treatment Terminations During Radiation Therapy: A 10-Year Experience

PURPOSE

Patients undergoing radiation therapy may terminate treatment for any number of reasons. The incidence of treatment termination (TT) during radiation therapy has not been studied. Herein, we present a cohort of TT at a large multicenter radiation oncology department over 10 years.

METHODS AND MATERIALS

TTs between January 2013 and January 2023 were prospectively analyzed as part of an ongoing departmental quality and safety program. TT was defined as any premature discontinuation of therapy after initiating radiation planning. The rate of TT was calculated as a percentage of all patients starting radiation planning. All cases were presented at monthly morbidity and mortality conferences with a root cause reviewed.

RESULTS

A total of 1448 TTs were identified out of 31,199 planned courses of care (4.6%). Six hundred eighty-six (47.4%) involved patients treated with curative intent, whereas 753 (52.0%) were treated with palliative intent, and 9 (0.6%) were treated for benign disease. The rate of TT decreased from 8.49% in 2013 to 3.02% in 2022, with rates decreasing yearly. The most common disease sites for TT were central nervous system (21.7%), head and neck (19.3%), thorax (17.5%), and bone (14.2%). The most common causes of TT were hospice and/or patient expiration (35.9%), patient choice unrelated to toxicity (35.2%), and clinician choice unrelated to toxicity (11.5%).

CONCLUSIONS

This 10-year prospective review of TTs identified a year-over-year decrease in TTs as a percentage of planned patients. This decrease may be associated with the addition of root cause reviews for TTs and discussions monthly at morbidity and mortality rounds, coupled with departmental upstream quality initiatives implemented over time. Understanding the reasons behind TTs may help decrease preventable TTs. Although some TTs may be unavoidable, open discourse and quality improvement changes effectively reduce TT incidents over time.

How accurate is clinical prognostication by oncologists during routine practice in a general hospital and can it be improved by a specific prognosis training programme: a prospective interventional study

OBJECTIVES

Oncologists need competence in clinical prognostication to deliver appropriate care to patients with cancer. Most studies on prognostication have been restricted to patients in palliative care settings. This paper investigates (1) the prognostic accuracy of physicians regarding a broad cohort of patients with cancer with a median life expectancy of >2 years and (2) whether a prognosis training can improve prognostication.

DESIGN

Prospective single-centre study comprising 3 phases, each lasting 1 month.

SETTING

Large teaching hospital, department of oncology and haematology, Germany.

PARTICIPANTS

18 physicians with a professional experience from entry level to 34 years. 736 patients with oncological and malignant haematological diseases.

INTERVENTIONS

Baseline prognostication abilities were recorded during an 'untrained' phase 1. As an intervention, a specific prognosis-training programme was implemented prior to phases 2 and 3. In phase 3, physicians had to provide additional estimates with the inclusion of electronic prognostic tools.

OUTCOME MEASURES

Prognostic estimates (PE) were collected using 'standard' surprise question (SQ), 'probabilistic' SQ (both for short-term prognostication up to 6 months) and clinician prediction of survival (CPS) (for long-term prognostication). Estimated prognoses were compared with observed survival. Phase 1 was compared with phases 2 and 3.

RESULTS

We included 2427 PE for SQ, 1506 for CPS and 800 for probabilistic SQ. Median OS was 2.5 years. SQ accuracy improved significantly (p<0.001) from 72.6% in phase 1 to 84.3% in phase 3. Probabilistic SQ in phase 3 showed 83.1% accuracy. CPS accuracy was 25.9% and could not be significantly improved. (Electronic) prognostic tools-used alone-performed significantly worse (p<0.0005) than physicians and-used by the clinicians-did not improve their performance.

CONCLUSION

A specific prognosis-training programme could improve short-term and intermediate-term prognostication. Improvement of long-term prognostication was not possible. Inexperienced residents as well as experienced oncologists benefited from training.

Health-related Quality of Life in Patients with Previously Treated Advanced Urothelial Carcinoma from EV-301: A Phase 3 Trial of Enfortumab Vedotin Versus Chemotherapy

BACKGROUND AND OBJECTIVE

In comparison to chemotherapy, enfortumab vedotin (EV) prolonged overall survival in patients with previously treated advanced urothelial carcinoma in EV-301. The objective of the present study was to assess patient experiences of EV versus chemotherapy using patient-reported outcome (PRO) analysis of health-related quality of life (HRQoL).

METHODS

For patients in the phase 3 EV-301 trial randomized to EV or chemotherapy we assessed responses to the validated European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (QLQ-C30) at baseline, weekly for the first 12 wk, and then every 12 wk until discontinuation. We analyzed the QLQ-C30 change from baseline to week 12, the confirmed improvement rate, and the time to improvement or deterioration.

KEY FINDINGS AND LIMITATIONS

Baseline PRO compliance rates were 91% for the EV arm (n = 301) and 89% for the chemotherapy arm (n = 307); the corresponding average rates from baseline to week 12 were 70% and 67%. Patients receiving EV versus chemotherapy had reduced pain (difference in change from baseline to week 12: -5.7, 95% confidence interval [CI] -10.8 to -0.7; p = 0.027) and worsening appetite loss (7.3, 95% CI 0.90-13.69; p = 0.026). Larger proportions of patients in the EV arm reported HRQoL improvement from baseline than in the chemotherapy arm; the odds of a confirmed improvement across ten QLQ-C30 function/symptom scales were 1.67 to 2.76 times higher for EV than for chemotherapy. Patients in the EV arm had a shorter time to first confirmed improvement in global health status (GHS)/QoL, fatigue, pain, and physical, role, emotional, and social functioning (all p < 0.05). EV delayed the time to first confirmed deterioration in GHS/QoL (p = 0.027), but worsening appetite loss occurred earlier (p = 0.009) in comparison to chemotherapy.

CONCLUSIONS AND CLINICAL IMPLICATIONS

HRQoL with EV was maintained, and deterioration in HRQoL was delayed with EV in comparison to chemotherapy. Better results with EV were reported for some scales, with the greatest difference observed for pain. These findings reinforce the EV safety and efficacy outcomes and benefits observed in EV-301.

PATIENT SUMMARY

Patients with previously treated advanced cancer of the urinary tract receiving the drug enfortumab vedotin maintained their HRQoL in comparison to patients treated with chemotherapy. The EV-301 trial is registered on ClinicalTrials.gov as NCT03474107 and on EudraCT as 2017-003344-21.

Explainable Machine Learning Model to Predict Overall Survival in Patients Treated With Palliative Radiotherapy for Bone Metastases

PURPOSE

The estimation of prognosis and life expectancy is critical in the care of patients with advanced cancer. To aid clinical decision making, we build a prognostic strategy combining a machine learning (ML) model with explainable artificial intelligence to predict 1-year survival after palliative radiotherapy (RT) for bone metastasis.

MATERIALS AND METHODS

Data collected in the multicentric PRAIS trial were extracted for 574 eligible adults diagnosed with metastatic cancer. The primary end point was the overall survival (OS) at 1 year (1-year OS) after the start of RT. Candidate covariate predictors consisted of 13 clinical and tumor-related pre-RT patient characteristics, seven dosimetric and treatment-related variables, and 45 pre-RT laboratory variables. ML models were developed and internally validated using the Python package. The effectiveness of each model was evaluated in terms of discrimination. A Shapley Additive Explanations (SHAP) explainability analysis to infer the global and local feature importance and to understand the reasons for correct and misclassified predictions was performed.

RESULTS

The best-performing model for the classification of 1-year OS was the extreme gradient boosting algorithm, with AUC and F1-score values equal to 0.805 and 0.802, respectively. The SHAP technique revealed that higher chance of 1-year survival is associated with low values of interleukin-8, higher values of hemoglobin and lymphocyte count, and the nonuse of steroids.

CONCLUSION

An explainable ML approach can provide a reliable prediction of 1-year survival after RT in patients with advanced cancer. The implementation of SHAP analysis provides an intelligible explanation of individualized risk prediction, enabling oncologists to identify the best strategy for patient stratification and treatment selection.

Time estimates in prognostic discussions: A conversation analytic study of hospice multidisciplinary team meetings

BACKGROUND

Recommendations state that multidisciplinary team expertise should be utilised for more accurate survival predictions. How the multidisciplinary team discusses prognoses during meetings and how they reference time, is yet to be explored.

AIM

To explore how temporality is conveyed in relation to patients' prognoses during hospice multidisciplinary team meetings.

DESIGN

Video-recordings of 24 hospice multidisciplinary team meetings were transcribed and analysed using Conversation Analysis.

SETTING/PARTICIPANTS

A total of 65 staff participating in multidisciplinary team meetings in a UK hospice from May to December 2021.

RESULTS

Team members conveyed temporality in three different ways. (i) Staff stated that a patient was dying as part of the patient's current health status. These formulations did not include a time reference per se but described the patient's current situation (as dying) instead. (ii) Staff used specific time period references where another specific reference had been provided previously that somehow constrained the timeframe. In these cases, the prognosis would conflict with other proposed care plans. (iii) Staff members used unspecific time period references where the reference appeared vague and there was greater uncertainty about when the patient was expected to die.

CONCLUSIONS

Unspecific time period references are sufficient for achieving meaningful prognostic talk in multidisciplinary teams. In-depth discussion and accurate prediction of patient prognoses are not deemed a priority nor a necessity of these meetings. Providing precise predictions may be too difficult due to uncertainty and accountability. The lack of staff pursuing more specific time references implies shared knowledge between staff and a context-specific use of prognostic estimates.

A Systematic Review of Prognostic Factors in Patients with Cancer Receiving Palliative Radiotherapy: Evidence-Based Recommendations

(1) Background: Prognostication in patients with cancer receiving palliative radiotherapy remains a challenge. To improve the process, we aim to identify prognostic factors in this population from the literature and offer evidence-based recommendations on prognostication in patients undergoing palliative radiotherapy for non-curable or advanced cancers. (2) Methods: A systematic review was performed on the medical literature from 2005 to 2023 to extract papers on the prognosis of palliative radiotherapy patients with advanced cancer. The initial selection was performed by at least two authors to determine study relevance to the target area. Studies were then classified based on type and evidence quality to determine final recommendations. (3) Results: The literature search returned 57 papers to be evaluated. Clinical and biological prognostic factors were identified from these papers to improve clinical decision making or construct prognostic models. Twenty prognostic models were identified for clinical use. There is moderate evidence supporting (i) evidence-based factors (patient, clinical, disease, and lab) in guiding decision making around palliative radiation; (ii) that certain biological factors are of importance; (iii) prognostication models in patients with advanced cancer; and that (iv) SBRT or re-irradiation use can be guided by predictions of survival by prognostic scores or clinicians. Patients with more favorable prognoses are generally better suited to SBRT or re-irradiation, and the use of prognostic models can aid in this decision making. (4) Conclusions: This evaluation has identified several factors or tools to aid in prognosis and clinical decision making. Future studies should aim to further validate these tools and factors in a clinical setting, including the leveraging of electronic medical records for data availability. To increase our understanding of how causal factors interact with palliative radiotherapy, future studies should also examine and include prediction of response to radiation as an outcome.

Qualitative analysis of expressions used in the end-of-life discussions and their associated factors

OBJECTIVES

Discussing end-of-life (EOL) issues with patients remains challenging for health professionals. Physicians may use various expressions, including euphemistic ones, when disclosing the prognosis to their patients to reduce their psychological impact. However, the actual expressions of EOL disclosure in clinical practice are unclear. This study aims to investigate the expressions used in EOL disclosures and explore their associated factors.

METHODS

A retrospective chart review was conducted enrolling all the patients who died in a university-affiliated hospital. Expressions used in the EOL disclosure were qualitatively analyzed. The patients' participation rate and length from the discussion to death were investigated.

RESULTS

EOL disclosures were observed in 341 of 358 patients. The expressions used by the physicians were categorized into 4 groups; Group 1: Clear presentation of life expectancy (n = 106; 31.1%), Group 2: Euphemistic presentation of life expectancy (n = 24; 7.0%), Group 3: Presentation of risk of sudden death (n = 147; 43.1%), Group 4: No mention on life expectancy (n = 64; 18.8%). The proportion of male patients was higher in Group 2 (79%) and lower in Group 4 (56%). Patients with cancer accounted for approximately 70% of Groups 1 and 4, but only approximately 30% of Group 3. The patient participation rate was highest in Group4 (84.4%), followed by Group 2 (50.0%). The median time from EOL disclosure to death was longer in Groups 1 and 4 (26 and 29.5 days, respectively), compared to Groups 2 and 3 (18.5 and 16 days, respectively).

SIGNIFICANCE OF RESULTS

A variety of expressions are used in EOL disclosure. Patterns of communication are influenced by patients' gender and type of illness (cancer or noncancer). Euphemisms do not seem to facilitate timely disclosure of life expectancy or patient participation. For health professionals, not only devising the expressions to alleviate their patients' distress when breaking bad news but also considering the communication process and patient background are essential.

The value of performance status in predicting venous thromboembolism in lung cancer patients treated with immune checkpoint inhibitors

INTRODUCTION

The incidence of venous thromboembolism (VTE) is notably high in lung cancer patients, particularly among those treated with immune checkpoint inhibitors (ICIs). Previous studies have focused on the relationship between Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) and VTE risk in immune checkpoint inhibitor therapy, but available evidence is inconsistent.

METHODS

The clinical data of lung cancer patients treated with ICIs were collected and analyzed from West China Hospital between January 2018 and March 2022. ECOG PS score was measured on admission. The primary outcome was the incidence of VTE, encompassing both deep vein thrombosis (DVT) and pulmonary embolism (PE). Multivariate logistic regression analysis was conducted to calculate the odds ratio (OR) and 95% confidence interval (95% CI).

RESULTS

A total of 1115 lung cancer patients receiving ICIs were eligible for this study, VTE developed in 105 (9.4%) during the 12-month follow-up, of which 95 (8.5%) had DVT,14 (1.3%) had definite PE. Poor ECOG PS (PS ≥ 2) was associated with an increased risk for VTE (OR = 5.405, 95% CI = 3.067-9.525, P < 0.001), DVT (OR = 4.669, 95% CI = 2.588-8.427, P < 0.001) and PE (OR = 8.413, 95% CI = 2.565-27.600, P < 0.001) after multivariable adjustment in the study cohort.

CONCLUSION

VTE occurred in 9.4% of lung cancer patients treated with ICIs, and poor performance status was associated with an increased risk of VTE.

Aggressive anticancer treatment in the last 2 weeks of life

BACKGROUND

There is a concern that terminally ill cancer patients may be aggressively treated due to the rapidly growing possibilities of anticancer treatment. The aim of this study was to evaluate the use of anticancer treatment at the end of life (EoL).

MATERIALS AND METHODS

This retrospective study included adult patients with advanced solid cancers who were treated at the Institute of Oncology Ljubljana and died of cancer between January 2015 and December 2019. A multiple logistic regression model was used to assess an association between the aggressiveness of anticancer treatment (i.e. systemic therapy, radiotherapy and surgery) in the last 2 weeks of life and year of death, age at death, sex, prognosis of cancer and enrolment into the specialist palliative care (SPC).

RESULTS

We included 1736 patients in our analysis. Overall, 13.7% of patients were enrolled into the SPC and 14.4% received anticancer treatment in the last 2 weeks of life. The odds of receiving anticancer treatment significantly increased over time [odds ratio (OR) 1.15, 95% confidence interval (CI) 1.04-1.27]. There was an increased use of novel systemic therapy (e.g. small-molecule targeted therapy and immunotherapy) at the EoL. Older patients had significantly lower odds to receive anticancer treatment in the last 2 weeks of life as compared to younger patients (OR 0.96, 95% CI 0.95-0.98). As compared to patients receiving only a standard oncology care, those also enrolled into the SPC had significantly lower odds for anticancer treatment in the last 2 weeks of life (OR 0.22, 95% CI 0.12-0.43).

CONCLUSIONS

Terminally ill cancer patients have increased odds for receiving anticancer treatment, especially novel systemic therapies, in the last 2 weeks of life. Younger patients and those not enrolled into the SPC are at particular risk for anticancer treatment at the EoL.

Audit of 30-day mortality following palliative radiotherapy: are we able to improve patient care at the end of life?

Background

Several measurements defining the expected 30-day mortality (30-DM) to use in audit of radiation oncology departments have been proposed. However, its external validity is limited because of the lack of data from non-English speaking countries. This study assessed 30-DM in patients treated with palliative radiotherapy (PRT) in a Chilean-reference radiotherapy centre and explored if there had been tailored treatment at the end of life.

Materials and methods

Retrospective data collection was carried out for all patients treated at our institution between 1st January 2018 and 31st December 2021. Individual factors were modelled first to check for univariate association with 30-DM, those variables with a significance level of < 0.05 were considered for the final multivariable model.

Results

3,357 patients were included. The most common primary malignancies were breast (22%) and lung (16.1%). The most common treatment sites were bone (47.7%) and brain (12.2%). Overall, 30-DM was 14.7%, this rate was higher in patients treated for brain metastases (25.7%) and thoracic palliation (22.1%). 30-DM was associated with poor performance status (p < 0.01), lung and esophageal-gastric cancer (p = 0.04 and p = 0.02, respectively), metastases other than bone (p < 0.01), brain metastases (p < 0.01) and private health insurance (p <0.01).

Conclusions

In patients treated for brain metastasis and thoracic palliation 30-DM was higher than suggested benchmarks. Moreover, in these groups long courses of PRT were often performed. Audit data should be useful for planning interventions that improve selection of patients and prompting review of policies for indication and fractionation schedules of PRT.

The Incidence and Management of Cancer-Related Anorexia During Treatment with Vascular Endothelial Growth Factor Receptor-Tyrosine Kinase Inhibitors

Cancer-related anorexia is a common complication and frequently occurs in cancer patients treated with vascular endothelial growth factor receptor-tyrosine kinase inhibitors (VEGFR-TKIs). Anorexia contributes to malnutrition, body weight loss, and cachexia in affected patients. Furthermore, patients who experience anorexia have worse outcomes than those who maintain their appetite, highlighting the importance of managing anorexia and related symptoms. However, as the causes of anorexia are both diverse and interconnected, there have been challenges in evaluating and implementing effective interventions. In this review, we described the contributing factors to cancer-related anorexia and reviewed recent literature for the frequency of anorexia symptoms in patients treated with VEGFR-TKIs. Additionally, we evaluated the evidence for current interventions and the potential benefits of multimodal and multidisciplinary approaches to care. The frequency of anorexia symptoms in patients who received VEGFR-TKIs ranged from 14%-58% for all-grade anorexia and 0%-6% for grade 3 or 4 anorexia. While many of the interventions for cancer-related anorexia have minimal benefit or adverse events, recent advances in our understanding of cancer-related anorexia suggest that multimodal therapy with multidisciplinary care is a promising avenue of investigation. Several studies currently underway are anticipated to further assess the effectiveness of multimodal approaches.

Thirty-day mortality in hospitalised patients with lung cancer: incidence and predictors

OBJECTIVES

Patients with lung cancer experience high rates of hospitalisation, mainly due to the high risk of complications that emerge during the natural history of the disease. We designed a retrospective, single-centre, observational study aimed at defining the clinical predictors of 30-day mortality in hospitalised patients with lung cancer.

METHODS

Clinical records from the first admission of patients with lung cancer to the oncology ward of the University Hospital of Parma from 1 January 2017 to 1 January 2022 were collected.

RESULTS

251 consecutive patients were enrolled at the time of data cut-off. In the univariate analysis, baseline clinical predictors of 30-day mortality were Eastern Cooperative Oncology Group performance status (ECOG PS) (≥2 vs 0-1: 27.5% vs 14.8%, p=0.028), high Blaylock Risk Assessment Screening Score (BRASS) (high vs intermediate-low: 34.3% vs 11.9%, p<0.001), presence of pain (yes vs no: 24.4% vs 11.7%, p=0.009), number of metastatic sites (≥3 vs <3: 26.5% vs 13.4%, p=0.017) and presence of bone metastases (yes vs no: 29.0% vs 10.8%, p=0.001). In the multivariate analysis, high BRASS remained significantly associated with increased 30-day mortality (high vs intermediate-low; OR 2.87, 95% CI 1.21 to 6.78, p=0.016).

CONCLUSION

Our results suggest that baseline poor ECOG PS, high BRASS, presence of pain, high tumour burden and presence of bone metastases could be used as clinical predictors of 30-day mortality in hospitalised patients with lung cancer. In particular, the BRASS scale should be used as a simple tool to predict 30-day mortality in hospitalised patients with lung cancer.

Performance of the Palliative Prognostic Index for cancer patients: A systematic review and meta-analysis

BACKGROUND

Clinician predicted survival for cancer patients is often inaccurate, and prognostic tools may be helpful, such as the Palliative Prognostic Index (PPI). The PPI development study reported that when PPI score is greater than 6, it predicted survival of less than 3 weeks with a sensitivity of 83% and specificity of 85%. When PPI score is greater than 4, it predicts survival of less than 6 weeks with a sensitivity of 79% and specificity of 77%. However, subsequent PPI validation studies have evaluated various thresholds and survival durations, and it is unclear which is most appropriate for use in clinical practice. With the development of numerous prognostic tools, it is also unclear which is most accurate and feasible for use in multiple care settings.

AIM

We evaluated PPI model performance in predicting survival of adult cancer patients based on different thresholds and survival durations and compared it to other prognostic tools.

DESIGN

This systematic review and meta-analysis was registered in PROSPERO (CRD42022302679). We calculated the pooled sensitivity and specificity of each threshold using bivariate random-effects meta-analysis and pooled diagnostic odds ratio of each survival duration using hierarchical summary receiver operating characteristic model. Meta-regression and subgroup analysis were used to compare PPI performance with clinician predicted survival and other prognostic tools. Findings which could not be included in meta-analyses were summarised narratively.

DATA SOURCES

PubMed, ScienceDirect, Web of Science, CINAHL, ProQuest and Google Scholar were searched for articles published from inception till 7 January 2022. Both retrospective and prospective observational studies evaluating PPI performance in predicting survival of adult cancer patients in any setting were included. The Prediction Model Risk of Bias Assessment Tool was used for quality appraisal.

RESULTS

Thirty-nine studies evaluating PPI performance in predicting survival of adult cancer patients were included (n = 19,714 patients). Across meta-analyses of 12 PPI score thresholds and survival durations, we found that PPI was most accurate for predicting survival of <3 weeks and <6 weeks. Survival prediction of <3 weeks was most accurate when PPI score>6 (pooled sensitivity = 0.68, 95% CI 0.60-0.75, specificity = 0.80, 95% CI 0.75-0.85). Survival prediction of <6 weeks was most accurate when PPI score>4 (pooled sensitivity = 0.72, 95% CI 0.65-0.78, specificity = 0.74, 95% CI 0.66-0.80). Comparative meta-analyses found that PPI performed similarly to Delirium-Palliative Prognostic Score and Palliative Prognostic Score in predicting <3-week survival, but less accurately in <30-day survival prediction. However, Delirium-Palliative Prognostic Score and Palliative Prognostic Score only provide <30-day survival probabilities, and it is uncertain how this would be helpful for patients and clinicians. PPI also performed similarly to clinician predicted survival in predicting <30-day survival. However, these findings should be interpreted with caution as limited studies were available for comparative meta-analyses. Risk of bias was high for all studies, mainly due to poor reporting of statistical analyses. while there were low applicability concerns for most (38/39) studies.

CONCLUSIONS

PPI score>6 should be used for <3-week survival prediction, and PPI score>4 for <6-week survival. PPI is easily scored and does not require invasive tests, and thus would be easily implemented in multiple care settings. Given the acceptable accuracy of PPI in predicting <3- and <6-week survival and its objective nature, it could be used to cross-check clinician predicted survival especially when clinicians have doubts about their own judgement, or when clinician estimates seem to be less reliable. Future studies should adhere to the reporting guidelines and provide comprehensive analyses of PPI model performance.

Development and external validation of a predictive multivariable model for last-weeks survival of advanced cancer patients in the palliative home care setting (PACS)

PURPOSE

Various prognostic indexes have been proposed to improve physicians' ability to predict survival time in advanced cancer patients, admitted to palliative care (PC) with a survival probably to a few weeks of life, but no optimal score has been identified. The study aims therefore to develop and externally validate a new multivariable predictive model in this setting.

METHODS

We developed a model to predict short-term overall survival in cancer patients on the basis of clinical factors collected at PC admission. The model was developed on 1020 cancer patients prospectively enrolled to home palliative care at VIDAS Milan, Italy, between May 2018 and February 2020 and followed-up to June 2020, and validated in two separate samples of 544 home care and 247 hospice patients.

RESULTS

Among 68 clinical factors considered, five predictors were included in the predictive model, i.e., rattle, heart rate, anorexia, liver failure, and the Karnofsky performance status. Patient's survival probability at 5, 15, 30 and 45 days was estimated. The predictive model showed a good calibration and moderate discrimination (area under the receiver operating characteristic curve between 0.72 and 0.79) in the home care validation set, but model calibration was suboptimal in hospice patients.

CONCLUSIONS

The new multivariable predictive model for palliative cancer patients' survival (PACS model) includes clinical parameters routinely at patient's admission to PC and can be easily used to facilitate immediate and appropriate short-term clinical decisions for PC cancer patients in the home setting.

Validation of Modified Models of Objective Prognostic Score in Patients With Advanced Cancer

Background: The objective prognostic score (OPS) needs to be modified to reflect practical palliative care circumstances. Objectives: We aimed to validate modified models of OPS with few or no laboratory tests for patients with advanced cancer. Design: An observational study was performed. Setting/Subjects: A secondary analysis of an international, multicenter cohort study of patients in East Asia was performed. The subjects were inpatients with advanced cancer in the palliative care unit. Measurements: We developed two modified OPS (mOPS) models to predict two-week survival: mOPS-A consisted of two symptoms, two objective signs, and three laboratory results, while mOPS-B consisted of three symptoms, two signs, and no laboratory data. We compared the accuracy of the prognostic models using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Calibration plots for two-week survival and net reclassification indices (NRIs) were compared for the two models. Survival differences between higher and lower score groups of each model were identified by the log-rank test. Results: We included a total of 1796 subjects having median survival of 19.0 days. We found that mOPS-A had higher specificity (0.805-0.836) and higher AUROCs (0.791-0.797). In contrast, mOPS-B showed higher sensitivity (0.721-0.725) and acceptable AUROCs (0.740-0.751) for prediction of two-week survival. Two mOPSs showed good concordance in calibration plots. Considering NRIs, replacing the original OPS with mOPSs improved overall reclassification (absolute NRI: 0.47-4.15%). Higher score groups of mOPS-A and mOPS-B showed poorer survival than those of lower score groups (p < 0.001). Conclusions: mOPSs used reduced laboratory data and had relatively good accuracy for predicting survival in advanced cancer patients receiving palliative care.

Utilization of End-of-Life Care Rooms by Patients Who Died in a Single Hospice Unit at a National University Hospital in South Korea

Purpose

For the dignity of patients nearing the end of their lives, it is essential to provide end-of-life (EoL) care in a separate, dedicated space. This study investigated the utilization of specialized rooms for dying patients within a hospice unit.

Methods

This retrospective study examined patients who died in a single hospice unit between January 1, 2017, and December 31, 2021. Utilizing medical records, we analyzed the circumstances surrounding death, the employment of specialized rooms for terminally ill patients, and the characteristics of those who received EoL care in a shared room.

Results

During the 1,825-day survey period, deaths occurred on 632 days, and 799 patients died. Of these patients, 496 (62.1%) received EoL care in a dedicated room. The average duration of using this dedicated space was 1.08 days. Meanwhile, 188 patients (23.5%) died in a shared room. Logistic regression analysis revealed that a longer stay in the hospice unit was associated with a lower risk of receiving EoL care in a shared room (odds ratio [OR]=0.98, 95% confidence interval [CI] 0.97~0.99; P=0.002). Furthermore, a higher number of deaths on the day a patient died was associated with a greater risk of receiving EoL care in a shared room (OR=1.66, 95% CI 1.33~2.08; P<0.001).

Conclusion

To ensure that more patients receive EoL care for an adequate duration in a private setting, additional research is necessary to increase the number of dedicated rooms and incorporate them into the hospice unit at an early stage.

Long-Term Effects of a Ketogenic Diet for Cancer

A ketogenic diet has been proposed as a potential supportive therapy for cancer patients, although its long-term influence on survival rates remain controversial. In our previous report, we presented promising results for 37 of 55 patients with advanced cancer enrolled between 2013 and 2018 who remained on a ketogenic diet for at least 3 months. We followed all 55 patients until March 2023 and analyzed the data up to March 2022. For the 37 patients with previously reported promising results, the median follow-up period was 25 (range of 3-104) months and 28 patients died. The median overall survival (OS) in this subset of 37 patients was 25.1 months and the 5-year survival rate was 23.9%. We also evaluated the association between the duration of the ketogenic diet and outcome in all 55 patients, except for 2 patients with insufficient data. The patients were divided into two groups: those who followed the diet for ≥12 months (n = 21) and those who followed it for <12 months (n = 32). The median duration of the ketogenic diet was 37 (range of 12-99) months for the ≥12 months group and 3 (range of 0-11) months for the <12 months group. During the follow-up period, 41 patients died (10/21 in the ≥12 months group and 31/32 in the <12 months group). The median OS was 19.9 months (55.1 months in the ≥12 months group and 12 months in the <12 months group). Following the inverse probability of treatment weighting to align the background factors of the two groups and make them comparable, the adjusted log-rank test showed a significantly better OS rate in the group that continued the ketogenic diet for a longer period (p < 0.001, adjusted log-rank test). These results indicate that a longer continuation of the ketogenic diet improved the prognosis of advanced cancer patients.

Prognostic evaluation in patients with advanced cancer in the last months of life: ESMO Clinical Practice Guideline

•This ESMO Clinical Practice Guideline provides key recommendations for using prognostic estimates in advanced cancer. •The guideline covers recommendations for patients with cancer and an expected survival of months or less. •An algorithm for use of clinical predictions, prognostic factors and multivariable risk prediction models is presented. •The author group encompasses a multidisciplinary group of experts from different institutions in Europe, USA and Asia. •Recommendations are based on available scientific data and the authors’ collective expert opinion.

Clinicians' Prediction of Survival and Prognostic Confidence in Patients with Advanced Cancer in Three East Asian Countries

Background: Little is known about accuracy and confidence of clinicians' prediction of survival (CPS) in East-Asian countries. Objective: We aimed to examine accuracy of CPS for 7-, 21-, and 42-day survival in palliative inpatients and its association with prognostic confidence. Design: An international prospective cohort study in Japan (JP), Korea (KR), and Taiwan (TW). Setting/Subjects: Subjects were inpatients with advanced cancer admitted to 37 palliative care units in three countries. Measurements: Discrimination of CPS was investigated through sensitivity, specificity, overall accuracy, and area under the receiver operating characteristics curves (AUROCs) according to 7-, 21-, and 42-day survival. The accuracies of CPS were compared with those of Performance Status-based Palliative Prognostic Index (PS-PPI). Clinicians were instructed to rate confidence level on a 0-10-point scale. Results: A total of 2571 patients were analyzed. The specificity was highest at 93.2-100.0% for the 7-day CPS, and sensitivity was highest at 71.5-86.8% for the 42-day CPS. The AUROCs of the seven-day CPS were 0.88, 0.94, and 0.89, while those of PS-PPI were 0.77, 0.69, and 0.69 for JP, KR, and TW, respectively. As for 42-day prediction, sensitivities of PS-PPI were higher than those of CPS. Clinicians' confidence was strongly associated with the accuracy of prediction in all three countries (all p-values <0.01). Conclusions: CPS accuracies were highest (0.88-0.94) for the seven-day survival prediction. CPS was more accurate than PS-PPI in all timeframe prediction except 42-day prediction in KR. Prognostic confidence was significantly associated with the accuracy of CPS.

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

BACKGROUND

Measuring the amount of physical activity and its patterns using wearable sensor technology in real-world settings can provide critical insights into health status.

OBJECTIVE

This study's aim was to develop and evaluate the analytical validity and transdemographic generalizability of an algorithm that classifies binary ambulatory status (yes or no) on the accelerometer signal from wrist-worn biometric monitoring technology.

METHODS

Biometric monitoring technology algorithm validation traditionally relies on large numbers of self-reported labels or on periods of high-resolution monitoring with reference devices. We used both methods on data collected from 2 distinct studies for algorithm training and testing, one with precise ground-truth labels from a reference device (n=75) and the second with participant-reported ground-truth labels from a more diverse, larger sample (n=1691); in total, we collected data from 16.7 million 10-second epochs. We trained a neural network on a combined data set and measured performance in multiple held-out testing data sets, overall and in demographically stratified subgroups.

RESULTS

The algorithm was accurate at classifying ambulatory status in 10-second epochs (area under the curve 0.938; 95% CI 0.921-0.958) and on daily aggregate metrics (daily mean absolute percentage error 18%; 95% CI 15%-20%) without significant performance differences across subgroups.

CONCLUSIONS

Our algorithm can accurately classify ambulatory status with a wrist-worn device in real-world settings with generalizability across demographic subgroups. The validated algorithm can effectively quantify users' walking activity and help researchers gain insights on users' health status.

Experience and perspectives of end-of-life care discussion and physician orders for life-sustaining treatment of Korea (POLST-K): a cross-sectional study

BACKGROUND

This study aimed to identify the healthcare providers' experience and perspectives toward end-of-life care decisions focusing on end-of-life discussion and physician's order of life-sustaining treatment documentation in Korea which are major parts of the Life-Sustaining Treatment Act.

METHODS

A cross-sectional survey was conducted using a questionnaire developed by the authors. A total of 474 subjects-94 attending physicians, 87 resident physicians, and 293 nurses-participated in the survey, and the data analysis was performed in terms of frequency, percentage, mean and standard deviation using the SPSS 24.0 program.

RESULTS

Study results showed that respondents were aware of terminal illness and physician's order of life-sustaining treatment in Korea well enough except for some details. Physicians reported uncertainty in terminal state diagnosis and disease trajectory as the most challenging. Study participants regarded factors (related to relationships and communications) on the healthcare providers' side as the major impediment to end-of-life discussion. Study respondents suggested that simplification of the process and more staff are required to facilitate end-of-life discussion and documentation.

CONCLUSION

Based on the study results, adequate education and training for better end-of-life discussion are required for future practice. Also, a simple and clear procedure for completing a physician's order of life-sustaining treatment in Korea should be prepared and legal and ethical advice would be required. Since the enactment of the Life-Sustaining Treatment Act, several revisions already have been made including disease categories, thus continuous education to update and support clinicians is also called for.

Prognostication in Advanced Cancer by Combining Actigraphy-Derived Rest-Activity and Sleep Parameters with Routine Clinical Data: An Exploratory Machine Learning Study

Survival prediction is integral to oncology and palliative care, yet robust prognostic models remain elusive. We assessed the feasibility of combining actigraphy, sleep diary data, and routine clinical parameters to prognosticate. Fifty adult outpatients with advanced cancer and estimated prognosis of <1 year were recruited. Patients were required to wear an Actiwatch® (wrist actigraph) for 8 days, and complete a sleep diary. Univariate and regularised multivariate regression methods were used to identify predictors from 66 variables and construct predictive models of survival. A total of 49 patients completed the study, and 34 patients died within 1 year. Forty-two patients had disrupted rest-activity rhythms (dichotomy index (I < O ≤ 97.5%) but I < O did not have prognostic value in univariate analyses. The Lasso regularised derived algorithm was optimal and able to differentiate participants with shorter/longer survival (log rank p < 0.0001). Predictors associated with increased survival time were: time of awakening sleep efficiency, subjective sleep quality, clinician’s estimate of survival and global health status score, and haemoglobin. A shorter survival time was associated with self-reported sleep disturbance, neutrophil count, serum urea, creatinine, and C-reactive protein. Applying machine learning to actigraphy and sleep data combined with routine clinical data is a promising approach for the development of prognostic tools.

Systemic Opioids for Dyspnea in Cancer Patients: A Real-world Observational Study

CONTEXT

Although Systemic opioids are recommended as a pharmacological treatment for cancer-related dyspnea, their effectiveness and safety needs to be investigated in a real-world context OBJECTIVES: To evaluate the effectiveness and safety of systemic regular opioids for dyspnea in cancer patients, in the real-world palliative care practice.

METHODS

This was a multicenter prospective observational study. We consecutively enrolled adult cancer patients starting regular opioids (morphine, oxycodone, hydromorphone, or fentanyl) for dyspnea from 12 palliative care services across Japan. We evaluated dyspnea intensity using the Numerical Rating Scale (NRS) and Integrated Palliative Outcome Scale (IPOS) every 24 hours until 72 hours after starting opioids (T1-T3). We also evaluated common opioid-related adverse events (AEs) and other severe AEs.

RESULTS

We enrolled 402 cancer patients. The proportion of responders was 68.8% (95%confidence intervals (CI): 0.63-0.74) at T1, 75.7% (95%CI: 0.70-0.81) at T2, and 82.1% (95%CI: 0.76-0.87) at T3. The mean differences in dyspnea NRS from baseline were 1.73 (95%CI: 1.46-1.99) at T1, 1.99 (95%CI: 1.71-2.28) at T2, and 2.47 (95%CI:2.13-2.82) at T3. The most common treatment-emergent AE was somnolence with an incidence of the severe form of approximately 10% throughout the study period. In the multivariate analysis, baseline dyspnea NRS ≥6 had a positive correlation with dyspnea relief by systemic regular opioids, while liver metastasis, clinician-predicted survival days, and opioid tolerance had a negative correlation.

CONCLUSION

Regular systemic opioids were effective for dyspnea in real-world cancer patients.

Prognostic value of the nutritional risk index in patients with newly diagnosed multiple myeloma

The nutritional risk index (NRI), which is based on weight and albumin levels, is closely associated with the prognosis of many cancers. However, its prognostic value has not been investigated in patients with newly diagnosed multiple myeloma (NDMM). We aimed to assess the association between the NRI and survival outcomes in patients with NDMM. We retrospectively collected and analyzed clinical and laboratory data from patients with NDMM between 2005 and 2019 at our center. Patients were stratified into the high NRI (> 89) and low NRI (≤ 89) groups for prognostic analysis. The NRI and other variables were also explored to evaluate their prognostic value for overall survival (OS). A total of 638 patients diagnosed with NDMM were retrospectively included. Patients in the high NRI group had a significantly better median OS than those in the low NRI group (64 months vs 43 months, p < 0.001). In the multivariate analysis, a high NRI was shown to be an independent prognostic factor for OS (hazard ratio, 0.758; 95% confidence interval, 0.587-0.977; p = 0.033). Age, performance status, transplant status, and lactate dehydrogenase level were also independent prognostic factors for OS. In conclusion, our study demonstrates that the NRI is a simple and useful predictor of survival outcomes in patients with NDMM.

Demystifying Prognosis : Understanding the Science and Art of Prognostication

The science of prognostication is emerging as a vital part of providing goal concordant patient care. Historically, modern medicine has tended to shy away from approaching prognostication as a core clinical skill, and prognosis as something to be shared directly with the patient. In recent years however, the medical field's shift towards a focus on patient autonomy and more openness in matters regarding end of life has propelled the study of prognostication into a more essential component of patient centered care. This calls for more emphasis on teaching the science of prognosis and the skill of prognostication as a core part of modern medical education. The following chapter aims to delve into the science of prognostication, explore the methods of formulating a prognosis, and discuss issues surrounding the communication of prognosis.

An online randomised controlled trial of prognosticating imminent death in advanced cancer patients: Clinicians give greater weight to advice from a prognostic algorithm than from another clinician with a different profession

BACKGROUND

A second opinion or a prognostic algorithm may increase prognostic accuracy. This study assessed the level to which clinicians integrate advice perceived to be coming from another clinician or a prognostic algorithm into their prognostic estimates, and how participant characteristics and nature of advice received affect this.

METHODS

An online double-blind randomised controlled trial was conducted. Palliative doctors, nurses and other types of healthcare professionals were randomised into study arms differing by perceived source of advice (algorithm or another clinician). In fact, the advice was the same in both arms (emanating from the PiPS-B14 prognostic model). Each participant reviewed five patient summaries. For each summary, participants: (1) provided an initial probability estimate of two-week survival (0% 'certain death'-100% 'certain survival'); (2) received advice (another estimate); (3) provided a final estimate. Weight of Advice (WOA) was calculated for each summary (0 '100% advice discounting' - 1 '0% discounting') and multilevel linear regression analyses were conducted.

CLINICAL TRIAL REGISTRATION NUMBER

NCT04568629.

RESULTS

A total of 283 clinicians were included in the analysis. Clinicians integrated advice from the algorithm more than advice from another clinician (WOA difference = -0.12 [95% CI -0.18, -0.07], p < 0.001). There was no interaction between study arm and participant profession, years of palliative care or overall experience. Advice of intermediate strength (75%) was given a lower WOA (0.31) than advice received at either the 50% (WOA 0.40) or 90% level (WOA 0.43). The overall interaction between strength of advice and study arm on WOA was significant (p < 0.001).

CONCLUSION

Clinicians adjusted their prognostic estimates more when advice was perceived to come from a prognostic algorithm than from another clinician. Research is needed to understand how clinicians make prognostic decisions and how algorithms are used in clinical practice.

Outcome of Hospitalized Cancer Patients with Hypernatremia: A Retrospective Case-Control Study

Hypernatremia (>145 mmol/L) is a relatively rare event, and the data regarding its role in the outcome of inpatients on an oncology ward are weak. The aim of this study was to describe the prevalence, prognosis, and outcome of hospitalized cancer patients with hypernatremia. We performed a retrospective case-control study of data obtained from inpatients with a solid tumor at the St. Claraspital, Basel, Switzerland, who were admitted between 2017 and 2020. The primary endpoint was overall survival. Hypernatremia was found in 93 (3.16%) of 2945 inpatients bearing cancer or lymphoma. From 991 eligible normonatremic control patients, 93 were matched according to diagnosis, age, and sex. The median overall survival time (OS) of patients with hypernatremia was 1.5 months compared to 11.7 months of the normonatremic controls (HR 2.69, 95% CI 1.85-3.90, p < 0.0001). OS of patients with irreversible compared to reversible hypernatremia was significantly shorter (23 versus 88 days, HR 4.0, 95% CI 2.04-7.70, p < 0.0001). The length of hospital stay was significantly longer for the hypernatremic than for the normonatremic group (p < 0.0001). Significantly more patients with hypernatremia died in the hospital (30.1% versus 8.6%, p < 0.001). These results suggest hypernatremia to be associated with an unfavorable outcome and a very short OS.

Malnutrition among Cancer Patients in a Tertiary Care Centre: A Descriptive Cross-sectional Study

Introduction

Malnutrition is one of the most frequent disorders among cancer patients. It is seen in 50-90% of cancer patients. This high prevalence of malnutrition is very concerning as it is associated with reduced effective treatment, functional status, quality of life and survival. The aim of the study was to find out the prevalence of malnutrition among cancer patients in a tertiary care centre.

Methods

A descriptive cross-sectional study was conducted among 95 cancer patients in the Department of Clinical Oncology of a tertiary care centre from 25 January 2022 to 25 July 2022. Ethical approval was obtained from the Institutional Review Committee (Reference number: 1192/2078/79). Convenience sampling was done. Patients were screened using Patient-Generated Subjective Global Assessment for malnutrition. Point estimate and 95% Confidence Interval were calculated.

Results

Among 95 cancer patients, 22 (23.15%) (15.10-32.90, 95% Confidence Interval) were malnourished.

Conclusions

The prevalence of malnutrition was found to be lower than in other studies done in similar settings. Nutritional assessment and support should be an integral part of care for gastrointestinal cancer.

Keywords

malnourishment; nutritional deficiency; screening.

Comparison of Objective Prognostic Score and Palliative Prognostic Score performance in inpatients with advanced cancer in Japan and Korea

OBJECTIVE

Accurate prognostication is important for patients and their families to prepare for the end of life. Objective Prognostic Score (OPS) is an easy-to-use tool that does not require the clinicians' prediction of survival (CPS), whereas Palliative Prognostic Score (PaP) needs CPS. Thus, inexperienced clinicians may hesitate to use PaP. We aimed to evaluate the accuracy of OPS compared with PaP in inpatients in palliative care units (PCUs) in three East Asian countries.

METHOD

This study was a secondary analysis of a cross-cultural, multicenter cohort study. We enrolled inpatients with far-advanced cancer in PCUs in Japan, Korea, and Taiwan from 2017 to 2018. We calculated the area under the receiver operating characteristics (AUROC) curve to compare the accuracy of OPS and PaP.

RESULTS

A total of 1,628 inpatients in 33 PCUs in Japan and Korea were analyzed. OPS and PaP were calculated in 71.7% of the Japanese patients and 80.0% of the Korean patients. In Taiwan, PaP was calculated for 81.6% of the patients. The AUROC for 3-week survival was 0.74 for OPS in Japan, 0.68 for OPS in Korea, 0.80 for PaP in Japan, and 0.73 for PaP in Korea. The AUROC for 30-day survival was 0.70 for OPS in Japan, 0.71 for OPS in Korea, 0.79 for PaP in Japan, and 0.74 for PaP in Korea.

SIGNIFICANCE OF RESULTS

Both OPS and PaP showed good performance in Japan and Korea. Compared with PaP, OPS could be more useful for inexperienced physicians who hesitate to estimate CPS.

Effect of heated humidified high-flow nasal cannula (HFNC) oxygen therapy in dyspnea patients with advanced cancer, a randomized controlled clinical trial

PURPOSE

Heated humidified high-flow nasal cannula (HFNC) oxygen therapy is one of the most important oxygen therapy methods, which are commonly applied to relieve dyspnea in advanced cancer patients. Our study aims to observe the efficacy and safety of HFNC oxygen therapy on dyspnea patients with advanced cancer and explore the clinical application.

METHODS

Sixty subjects with advanced cancer requiring oxygen therapy from a grade 3, class A hospital in China were recruited and randomized (1:1) to traditional nasal catheter oxygen therapy or HFNC. Primary outcomes were dyspnea, oral dryness, and sleep condition, which were recorded after 72-h treatment. Secondary outcomes were heart rate (HR), respiration rate (RR), S_pO₂, P_aO₂, and P_aCO₂, which were recorded after 2, 6, 24, and 72 h treatment.

RESULTS

Seventy-two hours after treatment, there were significant improvements in all primary outcomes (P < 0.001). P_aO₂ and RR were statistically changed 2 h after HFNC treatment (P < 0.001). P_aCO₂ and HR were statistically changed 24 h after HFNC treatment (P < 0.001).

CONCLUSION

HFNC oxygen therapy has good effect, high safety, and is easy to be accepted by dyspnea patients with advanced cancer. It can be used as the first choice of oxygen therapy for these patients and has broad clinical prospects.

TRIAL REGISTRATION

This work was retrospectively registered in the Chinese Clinical Trials Registry (ChiCTR2100049582) on August 4, 2021.

Prognostication in palliative radiotherapy—ProPaRT: Accuracy of prognostic scores

Background

Prognostication can be used within a tailored decision-making process to achieve a more personalized approach to the care of patients with cancer. This prospective observational study evaluated the accuracy of the Palliative Prognostic score (PaP score) to predict survival in patients identified by oncologists as candidates for palliative radiotherapy (PRT). We also studied interrater variability for the clinical prediction of survival and PaP scores and assessed the accuracy of the Survival Prediction Score (SPS) and TEACHH score.

Materials and methods

Consecutive patients were enrolled at first access to our Radiotherapy and Palliative Care Outpatient Clinic. The discriminating ability of the prognostic models was assessed using Harrell’s C index, and the corresponding 95% confidence intervals (95% CI) were obtained by bootstrapping.

Results

In total, 255 patients with metastatic cancer were evaluated, and 123 (48.2%) were selected for PRT, all of whom completed treatment without interruption. Then, 10.6% of the irradiated patients who died underwent treatment within the last 30 days of life. The PaP score showed an accuracy of 74.8 (95% CI, 69.5–80.1) for radiation oncologist (RO) and 80.7 (95% CI, 75.9–85.5) for palliative care physician (PCP) in predicting 30-day survival. The accuracy of TEACHH was 76.1 (95% CI, 70.9–81.3) and 64.7 (95% CI, 58.8–70.6) for RO and PCP, respectively, and the accuracy of SPS was 70 (95% CI, 64.4–75.6) and 72.8 (95% CI, 67.3–78.3).

Conclusion

Accurate prognostication can identify candidates for low-fraction PRT during the last days of life who are more likely to complete the planned treatment without interruption.

All the scores showed good discriminating capacity; the PaP had the higher accuracy, especially when used in a multidisciplinary way.

Association of Antipsychotic Dose With Survival of Advanced Cancer Patients With Delirium

CONTEXT

Delirium is common in patients with advanced cancer, and antipsychotics are widely used for its management.

OBJECTIVES

We aimed to explore the association of the antipsychotic dose with survival of terminally ill cancer patients with delirium.

METHODS

A secondary analysis of a multicenter prospective observational study was conducted. We enrolled adult advanced cancer patients who developed delirium and received antipsychotics at 14 palliative care units in Japan between September 2015 and May 2016. Hazard ratios of survival after starting antipsychotics between groups with different oral chlorpromazine equivalent doses: low: <100 mg, moderate: 100-200 mg, high: ≥200 mg, were calculated with adjustment for potential confounders using Cox regression. The antipsychotic dose-specific mortality risk was estimated with smooth splines.

RESULTS

Of 453 patients enrolled, 422 patients were analyzed. The median antipsychotic dose was 92.6 mg: low-dose (N = 231), moderate-dose (122), and high-dose (69). The median survival of all patients was 11 days. Compared with the low-dose group, the high-dose group showed a significantly shorter survival (HR: 1.46, 95%CI: 1.08-1.98). Smooth splines demonstrated that HR continuously increased as the antipsychotic dose increased. In patients treated with atypical antipsychotics, the high-dose group showed a significantly shorter survival than the low-dose group (HR: 2.86), while in patients treated with typical antipsychotics, survival was not significantly different (0.99).

CONCLUSIONS

Higher doses of antipsychotics were associated with increased mortality in terminally ill cancer patients with delirium. To minimize the potential mortality risk, antipsychotics should be started at low doses and titrated carefully.

Development and Validation of the PaP Score Nomogram for Terminally Ill Cancer Patients

The validated Palliative Prognostic (PaP) score predicts survival in terminally ill cancer patients, assigning patients to three different risk groups according to a 30-day survival probability: group A, >70%; group B, 30−70%; and group C, <30%. We aimed to develop and validate a PaP nomogram to provide individualized prediction of survival at 15, 30 and 60 days. Three cohorts of consecutive terminally ill cancer patients were used: one (n = 519) for nomogram development and internal validation, and a second (n = 451) and third (n = 549) for external validation. Multivariate analyses included dyspnea, anorexia, Karnofsky performance status, clinical prediction of survival, total white blood count and lymphocyte percentage. The predictive accuracy of the nomogram was determined by Harrell’s concordance index (95% CI), and calibration plots were generated. The nomogram had a concordance index of 0.74 (0.72−0.75) and showed good calibration. The internal validation showed no departures from ideal prediction. The accuracy of the nomogram at 15, 30 and 60 days was 74% (70−77), 89% (85−92) and 72% (68−76) in the external validation cohorts, respectively. The PaP nomogram predicts the individualized estimate of survival and could greatly facilitate clinical care decision-making at the end of life.

Fluorescence in situ hybridization detection of chromosome 7 and/or 17 polysomy as a prognostic marker for cholangiocarcinoma

Cholangiocarcinoma (CCA) is highly endemic in the Northeast Thailand. Recently, chromosome aberrations provided new insights into pathogenesis of CCA. Therefore, chromosome aberration might be used as a prognostic factor and therapeutic planning of this cancer. This aim of this study is to examine the correlation between an increase of chromosome 7 (C7) and/or 17 (C17) copy number variants (CNVs) with clinicopathological data and the overall survival time (OS) of CCA patients using fluorescence in situ hybridization (FISH) assays. C7 and C17 CNVs were examined using FISH form 157 formalin-fixed paraffin-embedded (FFPE) tissues of CCA patients from Khon Kaen, Thailand between 2011 and 2015. OS was visualized using Kaplan-Meier plot. Univariate and multivariate analyses were used to determine the ability of the clinicopathological parameters to predict OS. C17 > trisomy (odd ratio, 6.944, P < 0.001), C7/17 trisomy (odd ratio; 4.488, P = 0.019), and C7/17 > trisomy (odd ratio; 6.723, P < 0.001) were independently predictive factors for lymph node metastasis. Interestingly, an increase of C7, C17, and C7/17 CNVs in both trisomy and > trisomy was independently correlated with short median OS. An increased of C7 and/or 17 have a potential as a poor prognostic marker in CCA patients.

Tumor cell anabolism and host tissue catabolism-energetic inefficiency during cancer cachexia

Cancer-associated cachexia (CC) is a pathological condition characterized by sarcopenia, adipose tissue depletion, and progressive weight loss. CC is driven by multiple factors such as anorexia, excessive catabolism, elevated energy expenditure by growing tumor mass, and inflammatory mediators released by cancer cells and surrounding tissues. In addition, endocrine system, systemic metabolism, and central nervous system (CNS) perturbations in combination with cachexia mediators elicit exponential elevation in catabolism and reduced anabolism in skeletal muscle, adipose tissue, and cardiac muscle. At the molecular level, mechanisms of CC include inflammation, reduced protein synthesis, and lipogenesis, elevated proteolysis and lipolysis along with aggravated toxicity and complications of chemotherapy. Furthermore, CC is remarkably associated with intolerance to anti-neoplastic therapy, poor prognosis, and increased mortality with no established standard therapy. In this context, we discuss the spatio-temporal changes occurring in the various stages of CC and highlight the imbalance of host metabolism. We provide how multiple factors such as proteasomal pathways, inflammatory mediators, lipid and protein catabolism, glucocorticoids, and in-depth mechanisms of interplay between inflammatory molecules and CNS can trigger and amplify the cachectic processes. Finally, we highlight current diagnostic approaches and promising therapeutic interventions for CC.

Prevalence and predictors for 72-h mortality after transfer to acute palliative care unit

Purpose

Accurate prediction of survival is important to facilitate clinical decision-making and improve quality of care at the end of life. While it is well documented that survival prediction poses a challenge for treating physicians, the need for clinically valuable predictive factors has not been met. This study aims to quantify the prevalence of patient transfer 72 h before death onto the acute palliative care unit in a tertiary care center in Switzerland, and to identify factors predictive of 72-h mortality.

Methods

All patients hospitalized between January and December 2020 on the acute palliative care unit of the Competence Center Palliative Care of the Department of Radiation Oncology at the University Hospital Zurich were assessed. Variables were retrieved from the electronic medical records. Univariable and multivariable logistic regressions were used to identify predictors of mortality.

Results

A total of 398 patients were screened, of which 188 were assessed. Every fifth patient spent less than 72 h on the acute palliative care unit before death. In multivariable logistic regression analysis, predictors for 72-h mortality after transfer were no prior palliative care consult (p = 0.011), no advance care directive (p = 0.044), lower performance status (p = 0.035), lower self-care index (p = 0.003), and lower blood albumin level (p = 0.026).

Conclusion

Late transfer to the acute palliative care unit is not uncommon, which can cause additional distress to patients and caretakers. Though clinically practical short-term survival predictors remain largely unidentified, early integration of palliative care should be practiced more regularly in patients with life-limiting illness.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00520-022-07075-6.

Performance of clinician prediction of survival in oncology outpatients with advanced cancer

Background

We aimed to investigate the performance of clinician prediction of survival (CPS) and the association between CPS and the prognostic confidence of clinicians in ambulatory medical oncology outpatients.

Methods

Eight medical oncologists estimated the expected survival of their patients in a prospective cohort study. They were asked to provide a temporal type of CPS in weeks, together with their level of confidence for each prediction (0–100%). We analyzed the accuracy of CPS, the association between CPS and the prognostic confidence, and the characteristics of patients showing inaccurate CPS.

Results

A total of 200 advanced cancer patients were enrolled and the median overall survival was 7.6 months. CPS was accurate in 67 (33.5%) patients, underestimated in 87 (43.5%), and overestimated in 46 (23.0%). The overall accuracy of CPS for 12-week, 24-week, 36-week, and 48-week survival was 83.0%, 72.0%, 75.5%, and 74.0%, respectively. The specificity was highest for 12-week survival (90.2%) and the sensitivity was highest for 48-week survival (96.1%). The sensitivity of 12-week CPS was 51.4% and the area under the receiver operating characteristic (AUROC) curve was 0.79 (95% confidence interval [CI] 0.71–0.87). The prognostic confidence of clinicians was not significantly associated with the accuracy of prediction (P = 0.359). Patients with overestimated survival had significantly poorer global health status and physical/role/emotional functioning in the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Additionally, they showed significantly higher levels of fatigue, nausea/vomiting, pain, dyspnea, and loss of appetite.

Conclusion

The overall accuracy of CPS in predicting 12-week to 48-week survival was high in medical oncology outpatients. However the sensitivity of 12-week CPS was low and prognostic confidence was not associated with the accuracy of CPS. Patients with overestimated CPS showed poorer quality of life and higher symptom burden.

Prognostic decision-making about imminent death within multidisciplinary teams: a scoping review

OBJECTIVE

To summarise evidence on how multidisciplinary team (MDTs) make decisions about identification of imminently dying patients.

DESIGN

Scoping review.

SETTING

Any clinical setting providing care for imminently dying patients, excluding studies conducted solely in acute care settings.

DATA SOURCES

The databases AMED, CINAHL, Embase, MEDLINE, PsychINFO and Web of Science were searched from inception to May 2021.Included studies presented original study data written in English and reported on the process or content of MDT discussions about identifying imminently dying adult patients.

RESULTS

40 studies were included in the review. Studies were primarily conducted using interviews and qualitative analysis of themes.MDT members involved in decision-making were usually doctors and nurses. Some decisions focused on professionals recognising that patients were dying, other decisions focused on initiating specific end-of-life care pathways or clarifying care goals. Most decisions provided evidence for a partial collaborative approach, with information-sharing being more common than joint decision-making. Issues with decision-making included disagreement between staff members and the fact that doctors were often regarded as final or sole decision-makers.

CONCLUSIONS

Prognostic decision-making was often not the main focus of included studies. Based on review findings, research explicitly focusing on MDT prognostication by analysing team discussions is needed. The role of allied and other types of healthcare professionals in prognostication needs further investigation as well. A focus on specialist palliative care settings is also necessary.

Detection, Treatment, and Survival of Pancreatic Cancer Recurrence in the Netherlands: A Nationwide Analysis

OBJECTIVE

To evaluate whether detection of recurrent pancreatic ductal adenocarcinoma (PDAC) in an early, asymptomatic stage increases the number of patients receiving additional treatment, subsequently improving survival.

SUMMARY OF BACKGROUND DATA

International guidelines disagree on the value of standardized postoperative surveillance for early detection and treatment of PDAC recurrence.

METHODS

A nationwide, observational cohort study was performed including all patients who underwent PDAC resection (2014-2016). Prospective baseline and perioperative data were retrieved from the Dutch Pancreatic Cancer Audit. Data on follow-up, treatment, and survival were collected retrospectively. Overall survival (OS) was evaluated using multivariable Cox regression analysis, before and after propensity-score matching, stratified for patients with symptomatic and asymptomatic recurrence.

RESULTS

Eight hundred thirty-six patients with a median follow-up of 37 months (interquartile range 30-48) were analyzed. Of those, 670 patients (80%) developed PDAC recurrence after a median follow-up of 10 months (interquartile range 5-17). Additional treatment was performed in 159/511 patients (31%) with symptomatic recurrence versus 77/159 (48%) asymptomatic patients (P < 0.001). After propensity-score matching on lymph node ratio, adjuvant therapy, disease-free survival, and recurrence site, additional treatment was independently associated with improved OS for both symptomatic patients [hazard ratio 0.53 (95% confidence interval 0.42-0.67); P < 0.001] and asymptomatic patients [hazard ratio 0.45 (95% confidence interval 0.29-0.70); P < 0.001].

CONCLUSIONS

Additional treatment of PDAC recurrence was independently associated with improved OS, with asymptomatic patients having a higher probability to receive recurrence treatment. Therefore, standardized postoperative surveillance aiming to detect PDAC recurrence before the onset of symptoms has the potential to improve survival. This provides a rationale for prospective studies on standardized surveillance after PDAC resection.

Prediction of post-radiotherapy survival for bone metastases: a comparison of the 3-variable number of risk factors model with the new Katagiri scoring system

We investigated patient survival after palliative radiotherapy for bone metastases while comparing the prognostic accuracies of the 3-variable number of risk factors (NRF) model and the new Katagiri scoring system (Katagiri score). Overall, 485 patients who received radiotherapy for bone metastases were grouped as per the NRF model (groups I, II and III) and Katagiri score (low-, intermediate- and high-risk). Survival was compared using the log-rank or log-rank trend test. Independent prognostic factors were identified using multivariate Cox regression analyses (MCRA). MCRA and receiver operating characteristic (ROC) curves were used to compare both models' accuracy. For the 376 evaluable patients, the overall survival (OS) rates decreased significantly in the higher-tier groups of both models (P < 0.001). All evaluated factors except 'previous chemotherapy status' differed significantly between groups. Both models exhibited independent predictive power (P < 0.001). Per NRF model, hazard ratios (HRs) were 1.44 (P = 0.099) and 2.944 (P < 0.001), respectively, for groups II and III, relative to group I. Per Katagiri score, HRs for intermediate- and high-risk groups were 4.02 (P < 0.001) and 7.09 (P < 0.001), respectively, relative to the low-risk group. Areas under the curve (AUC) for predicting 6-, 18- and 24-month mortality were significantly higher when using the Katagiri score (P = 0.036, 0.039 and 0.022). Both models predict survival. Prognostic accuracy of the Katagiri score is superior, especially in patients with long-term survival potential; however, in patients with short prognosis, no difference occurred between both models; simplicity and patient burden should also be considered.

A prognostic model to identify short survival expectancy of medical oncology patients at the time of hospital discharge

Background

Hospitalization of cancer patients is associated with poor overall survival, but prognostic misclassification may lead to suboptimal therapeutic decisions and transitions of care. No model is currently available for stratifying the heterogeneous population of oncological patients after a hospital admission to a general Medical Oncology ward. We developed a multivariable prognostic model based on readily available and objective clinical data to estimate survival in oncological patients after hospital discharge.

Methods

A multivariable model and nomogram for overall survival after hospital discharge was developed in a retrospective training cohort and prospectively validated in an independent set of adult patients with solid tumors and a first admission to a unit of medical oncology. Performance of the model was assessed by C-index and Kaplan–Meier survival curves stratified by risk categories.

Results

From a population of 1089 patients with a first hospitalization, 757 patients were included in the training group [median survival, 43 weeks; 95% confidence interval (CI), 37-51 weeks] and 200 patients in the validation cohort (median survival, 44 weeks; 95% CI, 34 weeks-not reached). An accelerated failure time log-normal model was built, including five variables (primary tumor, stage, cause of admission, active treatment, and age). The C-index was 0.71 (95% CI, 0.69-0.73), with a good calibration, and adequate validation in the prospective cohort (C-index: 0.69; 95% CI, 0.65-0.74). Median survival in three predefined model-based risk groups was 10.7 weeks (high), 27.0 weeks (intermediate), and 3 years (low) in the training cohort, with comparable values in the validation cohort.

Conclusions

In oncological patients, individualized predictions of survival after hospitalization were provided by a simple and validated model. Further evaluation of the model might determine whether its use improves shared decision making at discharge.

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Hospitalization of poor prognosis oncology patients is a frequently missed opportunity for transition to palliative care.

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We developed and validated a prognostic index for cancer patients at hospital discharge based on five objective variables.

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Adequate prognostic stratification at discharge may facilitate transitions of care and shared decision making.

Lymphocyte percentage as a valuable predictor of prognosis in lung cancer

Lymphocytes and neutrophils are involved in the immune response against cancer. This study aimed to investigate the relationship between lymphocyte percentage/neutrophil percentage and the clinical characteristics of lung cancer patients, and to explore whether they could act as valuable predictors to ameliorate lung cancer prognosis. A total of 1312 patients were eligible to be recruited. Lymphocyte percentage and neutrophil percentage were classified based on their reference ranges. Survival curves were determined using Kaplan–Meier method, and univariate and multivariate cox regression analyses were performed to identify the significant predictors. Decision curve analysis was used to evaluate the clinical benefit. The results of both training and validation cohorts indicated that lymphocyte percentage exhibited high correlation with clinical characteristics and metastasis of lung cancer patients. Both lymphocyte percentage and neutrophil percentage were closely associated with survival status (all p < 0.0001). Low lymphocyte percentage could act as an indicator of poor prognosis; it offered a higher clinical benefit when combined with the clinical characteristic model. Our findings suggested that pretreatment lymphocyte percentage served as a reliable predictor of lung cancer prognosis, and it was also an accurate response indicator in lung adenocarcinoma and advanced lung cancer. Measurement of lymphocyte percentage improved the clinical utility of patient characteristics in predicting mortality of lung cancer patients.

Survival of patients with advanced cancer in Enteral Nutritional Therapy: a comparison between caloric estimates

ABSTRACT Objective To assess factors related to the achievement of the caloric estimates of enteral nutritional therapy and the survival of patients with advanced cancer in exclusively palliative care. Methods Retrospective study, where patients using enteral nutrition admitted from March 2019 to February 2020 were divided into two groups: Group 1 included patients who reached 75% of the estimated caloric goals, and Group 2 included those who did not. The data were extracted from the patients’ electronic medical records. Logistic regression analyzes were performed to assess associations between the studied sociodemographic, clinical, and nutritional variables, and the Kaplan-Meier curve and Cox regression were used to assess the survival of the groups. Results A total of 158 patients participated in the study, with a median age of 63 (IIQ: 55-70) years. 57% reached the caloric goal (Group 1). In the logistic regression, the functional capacity (OR: 5.82; CI: 2.28-14.84; p<0.001) and symptoms of nausea or vomiting (OR: 0.050; CI: 0.005-0.455; p=0.008) were independent variables for achieving the caloric goal. Cox regression showed Karnofsky Performance Status as an independent predictor for survival (HR: 1.85; CI: 1.13-3.04). Conclusion Patients with better functionality have longer survival and are potential candidates for reaching the caloric goals proposed by national and international guidelines for cancer patients.

Knowledge and use of prognostic scales by oncologists and palliative care physicians in adult patients with advanced cancer: A national survey (ONCOPRONO study)

BACKGROUND

Prognostic scales exist to estimate patient survival in advanced cancer. However, there are no studies evaluating their use and practice. The objective of this study was to evaluate in a nationwide study the proportion of oncologists and palliative care physicians who had knowledge of these scales.

METHODS

A descriptive, national, cross-sectional study was conducted via an online questionnaire to oncologists and palliative care physicians across France.

RESULTS

Palliative care physicians had better knowledge of the scales than oncologists (42.3% (n = 74) vs. 27.8% (n = 33), p = 0.015). The Palliative Performance Status (PPS) and Pronopall Scale were the best-known (51.4% (n = 55) and 65.4% (n = 70), respectively) and the most widely used (35% (n = 28) and 60% (n = 48), respectively). Improved training in the use of these scales was requested by 85.4% (n = 251) of participants, while 72.8% (n = 214) reported that they did not use them at all. Limited training and lack of consensus on which scale to use were cited as the main obstacles to use.

CONCLUSION

This is the first national study on the use of prognostic scales in advanced cancer. Our findings highlight a need to improve training in these scales and to reach a consensus on scale selection.

Comparison of the accuracy of clinicians' prediction of survival and Palliative Prognostic Score: an East Asian cross-cultural study

PURPOSE

No study has been conducted to compare the clinicians' prediction of survival (CPS) with Palliative Prognostic Scores (PaP) across countries. We aimed to compare the performance of the CPS in PaP (PaP-CPS), the PaP without the CPS, and the PaP total scores in patients with advanced cancer in three East Asian countries.

METHODS

We compared the discriminative accuracy of the three predictive models (the PaP-CPS [the score of the categorical CPS of PaP], the PaP without the CPS [sum of the scores of only the objective variables of PaP], and the PaP total score) in patients admitted to palliative care units (PCUs) in Japan, Korea, and Taiwan. We calculated the area under the receiver operating characteristic curve (AUROC) for 30-day survival to compare the discriminative accuracy of these three models.

RESULTS

We analyzed 2,072 patients from three countries. The AUROC for the PaP total scores was 0.84 in patients in Japan, 0.76 in Korea, and 0.79 in Taiwan. The AUROC of the PaP-CPS was 0.82 in patients in Japan, 0.75 in Korea, and 0.78 in Taiwan. The AUROC of the PaP without the CPS was 0.75 in patients in Japan, 0.66 in Korea, and 0.67 in Taiwan.

CONCLUSION

The PaP total scores and the PaP-CPS consistently showed similar discriminative accuracy in predicting 30-day survival in patients admitted to PCUs in Japan, Korea, and Taiwan. It may be sufficient for experienced clinicians to use the CPS alone for estimating the short-term survival (less than one month) of patients with far-advanced cancer. The PaP may help to improve prognostic confidence and further reduce subjective variations.