The art and science of prognosis in patients with advanced cancer

Shock Index Is a Validated Prediction Tool for the Short-Term Survival of Advanced Cancer Patients Presenting to the Emergency Department

Advanced cancer patients who are not expected to survive past the short term can benefit from early initiation of palliative care in the emergency department (ED). This discussion, however, requires accurate prognostication of their short-term survival. We previously found in our retrospective study that shock index (SI) is an ideal risk stratification tool in predicting the 60-day mortality risk of advanced cancer patients presenting to the ED. This study is a follow-up prospective validation study conducted from January 2019 to April 2021. A total of 410 advanced cancer patients who presented to the ED of a medical centre and could be followed-up feasibly were recruited. Univariate and multivariable logistic regression analyses were performed with receiver operator calibrating (ROC) curve analysis. Non-survivors had significantly lower body temperatures, higher pulse rates, higher respiratory rates, lower blood pressures, and higher SI. Each 0.1 increment of SI increased the odds of 60-day mortality by 1.591. Area under ROC curve was 0.7819. At optimal cut-off of 0.94, SI had 66.10% accuracy. These results were similar to our previous study, thus validating the use of SI in predicting the 60-day mortality of advanced cancer patients presenting to the ED. Identified patients may be offered palliative care.

Shock Index: A Simple and Effective Clinical Adjunct in Predicting 60-Day Mortality in Advanced Cancer Patients at the Emergency Department

Deciding between palliative and overly aggressive therapies for advanced cancer patients who present to the emergency department (ED) with acute issues requires a prediction of their short-term survival. Various scoring systems have previously been studied in hospices or intensive care units, though they are unsuitable for use in the ED. We aim to examine the use of a shock index (SI) in predicting the 60-day survival of advanced cancer patients presenting to the ED. Identified high-risk patients and their families can then be counseled accordingly. Three hundred and five advanced cancer patients who presented to the EDs of three tertiary hospitals were recruited, and their data retrospectively analyzed. Relevant data regarding medical history and clinical presentation were extracted, and respective shock indices calculated. Multivariate logistic regression analyses were performed. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive performance of the SI. Nonsurvivors within 60 days had significantly lower body temperatures and blood pressure, as well as higher pulse rates, respiratory rates, and SI. Each 0.1 SI increment had an odds ratio of 1.39 with respect to 60-day mortality. The area under the ROC curve was 0.7511. At the optimal cut-off point of 0.94, the SI had 81.38% sensitivity and 73.11% accuracy. This makes the SI an ideal evaluation tool for rapidly predicting the 60-day mortality risk of advanced cancer patients presenting to the ED. Identified patients can be counseled accordingly, and they can be assisted in making informed decisions on the appropriate treatment goals reflective of their prognoses.

Dorsal Muscle Attenuation May Predict Failure to Respond to Interleukin-2 Therapy in Metastatic Renal Cell Carcinoma

RATIONALE AND OBJECTIVES

To explore whether the sarcopenia body type can help predict response to interleukin-2 (IL-2) therapy in metastatic renal cell carcinoma (RCC).

MATERIALS AND METHODS

Institutional review board approval was obtained for this Health Insurance Portability and Accountability Act-compliant retrospective cohort study of 75 subjects with metastatic RCC who underwent pretreatment contrast-enhanced computed tomography within 1 year of initiating IL-2 therapy. Cross-sectional area and attenuation of normal-density (31-100 Hounsfield units [HU]) and low-density (0-30 HU) dorsal muscles were obtained at the T11 vertebral level. The primary outcome was partial or complete response to IL-2 using RECIST 1.1 criteria at 6 weeks. A conditional inference tree was used to determine an optimal HU cutoff for predicting outcome. Bonferroni-adjusted multivariate logistic regression was conducted to investigate the independent associations between imaging features and response after controlling for demographics, doses of IL-2, and RCC prognostic scales (eg, Heng and the Memorial Sloan Kettering Cancer Center [MSKCC]).

RESULTS

Most subjects had intermediate prognosis by Heng (65% [49 of 75]) and the MSKCC (63% [47 of 75]) criteria; 7% had complete response and 12% had partial response. Mean attenuation of low-density dorsal muscles was a significant univariate predictor of IL-2 response after Bonferroni correction (P = 0.03). The odds of responding to treatment were 5.8 times higher for subjects with higher-attenuation low-density dorsal muscles (optimal cutoff: 18.1 HU). This persisted in multivariate analysis (P = 0.02). Body mass index (P = 0.67) and the Heng (P = 0.22) and MSKCC (P = 0.08) clinical prognostic scales were not significant predictors of response.

CONCLUSIONS

Mean cross-sectional attenuation of low-density dorsal muscles (ie, sarcopenia) may predict IL-2 response in metastatic RCC. Clinical variables are poor predictors of response.

Worsening central sarcopenia and increasing intra-abdominal fat correlate with decreased survival in patients with adrenocortical carcinoma

BACKGROUND

Accurate prediction of survival from adrenocortical carcinoma (ACC) is difficult and current staging models are unreliable. Central sarcopenia as part of the cachexia syndrome is a marker of frailty and predicts mortality. This study seeks to confirm that psoas muscle density (PMD), lean psoas muscle area (LPMA), lumbar skeletal muscle index (LSMI), and intra-abdominal (IA) or subcutaneous fat (SC) can be used in combination to more accurately predict survival in ACC patients.

METHODS

PMD, LPMA, IA, and SC fat were measured on serial CT scans of patients with ACC. Clinical outcome was correlated with quantitative data from patients with ACC and analyzed. A linear regression model was used to describe the relationship between PMD, LPMA, LSMI, IA, and SC fat, time to recurrence, and length of survival according to tumor stage.

RESULTS

One hundred twenty-five ACC patients (94 females) were treated from 2005 to 2011. Significant morphometric predictors of survival include PMD, LPMA, and IA fat (p ≤ 0.0001, ≤ 0.0024, <0.0001, respectively) and improve prediction of survival compared to using stage alone. A 100-mm(2) increase in LPMA confers an 8 % lower hazard of death. LSMI does not change significantly between stages (p = 0.3196).

CONCLUSION

Decreased PMD, LPMA, and increased IA fat suggest decreased survival in ACC patients and correlate with traditional staging systems. A more precise prediction of survival may be achieved when staging systems and morphometric measures are used in combination. Serial measurements of morphometric data are possible. The rate of change of these variables over time may be more important than the absolute value.

An inflammation-based prognostic score and its role in the nutrition-based management of patients with cancer

Progressive involuntary weight loss, in particular the loss of lean tissue, is common in patients with advanced cancer and has long been recognised to result in a deterioration in performance status and quality of life, increased morbidity and mortality. The aetiology of such weight loss or cachexia is complex and involves both tumour and host responses. Thus, identification of patients who are or are likely to become cachectic has been problematic. In addition to a reduction in appetite and increased satiety leading to poor dietary intake, there is now increasing clinical evidence that the activation of a chronic ongoing systemic inflammatory response is one of the earliest and most important contributory factors to cachexia. Such findings help to explain the failure of simple nutritional programmes to reverse weight loss adequately in patients with cancer. In the present paper the development of an inflammation-based score is described, which is derived from the acute-phase proteins C-reactive protein and albumin and is termed the Glasgow prognostic score (GPS). Its value as a predictor of survival, independent of tumour stage, performance status and treatment (active or palliative), has been shown in a variety of advanced common solid tumours. The nature of the relationship between the GPS, appetite, body composition, performance status and quality of life of the patient with advanced cancer will be described. Recently, it has become evident that the systemic inflammatory response is also present in a smaller proportion of patients with primary operable cancer and is also predictive of disease progression and poor survival. The role of GPS in clinical decision making will be discussed.

Prognostic significance of symptoms of hospitalised advanced cancer patients

PURPOSE

To assess the prognostic value of symptoms in hospitalised advanced cancer patients.

PATIENTS AND METHODS

A prospective analysis was performed of 181 hospitalised patients referred to a Palliative Care Team. Comprehensive symptom questionnaire, functional status, estimated life expectancy and survival were assessed. Using a Cox regression model, a predictive survival model was built.

RESULTS

Median survival: 53 d. Median number of symptoms: 4; 20 symptoms occurred in 10%. Multivariate analysis showed nausea, dysphagia, dyspnoea, confusion and absence of depressed mood as independent prognostic factors for survival (p<0.05) with relative risks of dying of 1.96, 1.81, 1.79, 2.35 and 1.79, respectively. Patients with 2, 3 or 4 of these factors at the same time had a relative risk of dying of 2.7, 2.1 and 9.0, respectively.

CONCLUSION

A cluster of factors comprising nausea, dysphagia, dyspnoea, confusion and absence of depressed mood may be used to accurately predict survival in hospitalised advanced cancer patients.

Progressive disease in patients with cancer presenting to an emergency room with acute symptoms predicts short-term mortality

GOALS

Patients with symptomatic, advanced cancer continue to be referred late or not at all for hospice or palliative care. We conducted a retrospective cohort study to determine whether evidence of cancer progression is an independent predictor of short-term mortality in acutely symptomatic cancer patients.

PATIENTS AND METHODS

We reviewed the records of 396 patients who visited the emergency center at a comprehensive cancer center in January 2000. Records were reviewed for clinical characteristics, including symptoms, type and extent of cancer, and whether the patient's cancer was stable or progressing (uncontrolled) at the time of the emergency center visit. Cox regression analysis was used to assess survival at 90 and 180 days, after controlling for patient characteristics.

MAIN RESULTS

Patients who died within 14, 90, or 180 days were more likely to have disease progression than those who did not. Dyspnea on emergency center presentation and disease progression were independent predictors of death within 90 or 180 days, after controlling for patient age, symptoms, signs, and the presence of metastases. The odds ratios for death within 90 and 180 days were 3.97 and 4.34, respectively (95% confidence intervals: 1.44, 10.94 and 1.87, 10.09).

CONCLUSION

Cancer disease progression is a clinical measure of increased risk of short-term mortality in acutely symptomatic cancer patients. Future studies should examine whether the use of this characteristic enhances identification of patients who could benefit from timely referral to hospice or palliative care. Symptomatic cancer patients presenting to a cancer center emergency room were more likely to die within 14, 90, or 180 days if they had evidence of recent progression of their cancer. Among patients with disease progression, 47% died within 90 days and 61% within 180 days.

Setting up a palliative care clinic within a radiotherapy department: a model for developing countries

Nearly 50% of all newly diagnosed cancer patients in India (and other developing countries) are terminally ill with advanced disease. These patients are usually neglected or often receive futile anticancer treatment(s), whereas what they really need is maximum medical management in the form of palliative care and psychosocial support. Since advanced and incurable cancer cases are mostly referred for radiotherapy (RT), a palliative care (PC) clinic was started in the Department of Radiotherapy, PGIMER, Chandigarh. The PC clinic staff consisted of one specialist doctor, a nurse and volunteers. Previous disease and treatment records maintained by the RT colleagues were noted. Proforma-based assessments were done in the PC clinic and focused on patients' Karnofsky Performance Status, physical symptoms, drugs prescribed, and the doctor's or patient's/relative's response to/satisfaction with the treatment in each case. Prospective data on 100 patients (March to August 2001) revealed that various distressing physical symptoms (cachexia, dyspnoea, constipation) had not been routinely assessed earlier. Despite previous treatment, adequate pain management as per the WHO ladder was needed in 67 of 88 (76%) patients when they were seen by the PC team. On the regular follow-up visits to the PC clinic, 42% and 50% of the patients/relatives reported a response to and satisfaction with the treatment at their second and third visits. We believe two conclusions are justified. (1) Attention to palliative care needs could result in good treatment outcome and high level of patients' and doctors' satisfaction. (2) Since a specialist PC set-up is lacking in most medical institutions in India, the RT department is the best suited to delivery of palliative care for patients with advanced cancer.

A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

PURPOSE

To develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic.

METHODS AND MATERIALS

Sixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model.

RESULTS

Six prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS <or=13 (n = 133); 67%, 41%, and 20% for patients with SPS 14-19 (n = 129); and 36%, 18%, and 4% for patients with SPS >or=20 (n = 133) (p < 0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (<or=3 risk factors)(n = 98); 68%, 47%, and 24% (4 risk factors)(n = 117); and 46%, 24%, and 11% (>or=5 factors)(n = 180)(p < 0.0001).

CONCLUSION

Clinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use.