Risk Of Chemotherapy Toxicity Research Articles

Does routine clinical assessment of older adults with gastroesophageal cancer tell the whole story?

297 Background: Geriatric Assessment (GA) can help oncologists determine fitness of their older patients (pt) for anti-cancer therapy. Our objective was to compare routine provider assessment (PA) and GA of older adults with gastroesophageal cancer (GEC). Methods: Patients ≥65 with any stage of GEC completed a GA. The pt’s provider completed a PA and abnormalities detected by both assessments were centrally reviewed and compared. GA and PA assessed functional status, nutrition, comorbidities, psychological distress, cognition, social support, and chemotherapy toxicity risk. Validated assessment tools were used for the GA. Data collected 3 months post-enrollment included hospitalization, ≥ grade 3 toxicities, and treatment delays. We compared the proportions detected/not detected abnormalities by PA vs GA using McNemar’s test for paired data, and we measured agreement using Kappa statistics (1=full, 0=no, -1=disagreement). Results: 82 pts were enrolled, majority male (74%), median age 73 (65-91), stage III/IV (82%) disease on first line therapy (79%). Cancer sites included gastric (32%), esophageal (43%), GEJ (26%). Pts’ demographic and clinical characteristics did not predict for the identification of GA abnormalities. GA detected 196 abnormalities and PA detected 86. Majority of pts (84%) had ≥ 1 unidentified abnormality by PA. Providers identified more pts with clinically significant comorbidities as compared to GA. However, the GA identified more abnormalities compared to PA in all other evaluated domains (Table). Low agreement was found between PA and GA in any of the domains. Pts scoring high on the CARG chemotherapy toxicity prediction tool (p=0.004) and pts with evidence of psychological distress (p=0.049) had more ≥ grade 3 toxicity. Pts with abnormalities in functional status, nutrition, psychological distress, and a high CARG score were more likely to be hospitalized during therapy. Conclusions: Clinical characteristics of older pts with GEC are not predictive of GA abnormalities. While providers were better at identifying comorbidities, the GA resulted in a comprehensive evaluation of all domains and identified significant abnormalities that affect treatment outcomes in this population. [Table: see text]

SIOG2023-4-P-306 - Added value of serum albumin in refining chemotherapy toxicity risk prediction

SIOG2023-4-P-306 - Added value of serum albumin in refining chemotherapy toxicity risk prediction

Assessment of longitudinal changes in body composition of children with lymphoma and rhabdomyosarcoma.

Studies examining changes in skeletal muscle and adipose tissue during treatment for cancer in children, adolescents, and young adults and their effect on the risk of chemotherapy toxicity (chemotoxicity) are limited. Among 78 patients with lymphoma (79.5%) and rhabdomyosarcoma (20.5%), changes were measured in skeletal muscle (skeletal muscle index [SMI]; skeletal muscle density [SMD]) and adipose tissue (height-adjusted total adipose tissue [hTAT]) between baseline and first subsequent computed tomography scans at the third lumbar vertebral level by using commercially available software. Body mass index (BMI; operationalized as a percentile [BMI%ile]) and body surface area (BSA) were examined at each time point. The association of changes in body composition with chemotoxicities was examined by using linear regression. The median age at cancer diagnosis of this cohort (62.8% male; 55.1% non-Hispanic White) was 12.7 years (2.5-21.1 years). The median time between scans was 48days (range, 8-207 days). By adjusting for demographics and disease characteristics, this study found that patients undergo a significant decline in SMD (β ± standard error [SE]=-4.1±1.4; p<.01). No significant changes in SMI (β ± SE=-0.5±1.0; p=.7), hTAT (β ± SE=5.5±3.9; p=.2), BMI% (β ± SE=4.1±4.8; p=.3), or BSA (β ± SE=-0.02±0.01; p=.3) were observed. Decline in SMD (per Hounsfield unit) was associated with a greater proportion of chemotherapy cycles with grade ≥3 nonhematologic toxicity (β ± SE=1.09±0.51; p=.04). This study shows that children, adolescents, and young adults with lymphoma and rhabdomyosarcoma undergo a decline in SMD early during treatment, which is associated with a risk of chemotoxicities. Future studies should focus on interventions designed at preventing the loss of muscle during treatment. We show that among children, adolescents, and young adults with lymphoma and rhabdomyosarcoma receiving chemotherapy, skeletal muscle density declines early during treatment. Additionally, a decline in skeletal muscle density is associated with a greater risk of nonhematologic chemotoxicities.

External Validity of Two Scores for Predicting the Risk of Chemotherapy Toxicity Among Older Patients With Solid Tumors: Results From the ELCAPA Prospective Cohort.

Severe chemotherapy-related toxicities are frequent among older patients. The Chemotherapy Risk Assessment Scale for High-Age Patients (CRASH) and the Cancer and Aging Research Group Study (CARG) score were both developed to predict these events. The objective of this study was to evaluate the scores' predictive performance in a prospective cohort, which included patients aged 70 years and older referred for a geriatric assessment prior to chemotherapy for a solid tumor. The main endpoints were grades 3/4/5 toxicities for the CARG score and grades 4/5 hematologic toxicities and grades 3/4/5 non-hematologic toxicities for the CRASH score. A total of 248 patients were included, of which 150 (61%) and 126 (51%) experienced at least one severe adverse event as defined respectively in CARG and CRASH studies. The incidence of adverse events was not significantly greater in the intermediate and high-risk CARG groups than in the low-risk group (odds ratio (OR) [95% CI] = 0.3 [0.1-1.4] (P = .1) and 0.4 [0.1-1.7], respectively). The area under curve (AUC) was 0.55. Similarly, the incidence of severe toxicities was no greater in the intermediate-low, intermediate-high, and high-risk CRASH groups than in the low-risk CRASH group (OR [95%CI] = 1 [0.3-3.6], 1 [0.3-3.4], and 1.5 [0.3-8.1], respectively). The AUC was 0.52. The type of cancer, performance status, comorbidities, body mass index, and MAX2 index were independently associated with grades 3/4/5 toxicities. In an external cohort of older patients referred for a pretherapeutic GA, the CARG and CRASH scores were poor predictors of the risk of chemotherapy severe toxicities.

Chemotherapy Toxicity in Older Adults Optimized by Geriatric Assessment and Intervention: A Non-Comparative Analysis.

The Comprehensive Geriatric Assessment (CGA) is recommended to guide treatment choices in older patients with cancer. Patients ≥ 70 years referred to our oncology service with a new cancer diagnosis are screened using the G-8. Patients with a score of ≤14 are eligible to attend the Geriatric Oncology and Liaison (GOAL) Clinic in our institution, with referral based on physician discretion. Referred patients undergo multidimensional assessments at baseline. CGA domains assessed include mobility, nutritional, cognitive, and psychological status. Chemotherapy toxicity risk is estimated using the Cancer Aging and Research Group (CARG) calculator. We undertook a retrospective analysis of patients attending the GOAL clinic over a 30-month period to April 2021. The objective was to determine rates of treatment dose modifications, delays, discontinuation, and unscheduled hospitalizations as surrogates for cytotoxic therapy toxicity in these patients. These data were collected retrospectively. Ninety-four patients received chemotherapy; the median age was 76 (70–87) and 45 were female (48%). Seventy-five (80%) had an ECOG PS of 0–1. Seventy-two (77%) had gastrointestinal cancer, and most had stage III (47%) or IV (40%) disease. Chemotherapy with curative intent was received by 51% (n = 48) and 51% received monotherapy. From the CGA, the median Timed Up and Go was 11 s (7.79–31.6), and 90% reported no falls in the prior 6 months. The median BMI was 26.93 (15.43–39.25), with 70% at risk or frankly malnourished by the Mini Nutritional Assessment. Twenty-seven (29%) patients had impaired cognitive function. Forty-three (46%) had a high risk of toxicity based on the baseline CARG toxicity calculator. Twenty-six (28%) required dose reduction, 55% (n = 52) required a dose delay, and 36% (n = 34) had a hospitalization due to toxicity. Thirty-nine patients (42%) discontinued treatment due to toxicity. Despite intensive assessment, clinical optimization and personalized treatment decisions, older adults with cancer remain at high risk of chemotherapy toxicity.

Validation of the Cancer and Aging Research Group (CARG) model to identify risks of chemotherapy toxicities in Asian older adults.

12043 Background: Older adults are at an increased risk of chemotherapy related toxicities. Identification of risk factors can facilitate oncologists in tailoring treatment, potentially mitigate the risk of chemotherapy toxicity and improve social economic outcomes. Tools like the Karnofsky Performance Status (KPS) and Geriatric Assessment (GA) are used in clinical practice to guide treatment decisions for older adults with cancer. The CARG model incorporating the GA and clinical variables was developed and validated to predict for grade 3-5 toxicities, although this has not yet been validated in Asians. Methods: Patients ≥70 years old with solid malignancies receiving chemotherapy at the National University Cancer Institute, Singapore were recruited between June 2017 and January 2018. The study aims to verify the application of the CARG model, KPS, GA and oncologists’ estimate of toxicity in a multi-ethnic Asian population. The risks of chemotherapy toxicity were calculated using the CARG model (low risk: 0-5, medium risk: 6-9, high risk: ≥10). A GA including a physician rated KPS score (low risk: 90-100, medium risk:80, high risk: ≤70) and a timed up and go (TUG) test (low risk: ≤12s, high risk: &gt; 12s) were performed for all patients. The attending oncologist (blinded to the CARG score) was asked to give an estimated likelihood (low/medium/high) of chemotoxicity. Chemotherapy related toxicities were captured by chart review based on the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. The area under the receiver operating characteristic (ROC) curve and a univariate analysis of predictors of toxicity were calculated. Results: A total of 200 patients were included. Median age was 74 (range: 70-89). The ethnic makeup of the population consisted of Chinese (N = 177; 88.5%), Malay (N = 17; 8.5%), Indians (N = 4; 2%) and other ethnicities. Majority of patients were males (N = 110; 55%), had metastatic disease at diagnosis (N = 114; 57%) and had gastrointestinal cancers (N = 80; 40%). 75% (N = 150) had polychemotherapy and 55% (N = 110) received full dose chemotherapy. More than half of patients (68.5%) experienced G3-5 toxicities, with 65.5% requiring hospitalization. The CARG model predicted 22.5% of patients as low, 50.5% as medium and 27% as high risk of chemotoxicity. The area under ROC for the CARG model was 0.74 (95% CI, 0.67-0.82). A one-point increase in the CARG score was associated with a 15% increase in the odds of G3-5 toxicities. 84.5% of patients needed &gt; 12s for the TUG test. The TUG score, KPS and oncologist’s prediction of toxicity was predictive of an increased risk of G3-5 toxicities (p &lt; 0.01). Conclusions: This study confirms the validity of the CARG predictive model in Asians and can streamline healthcare delivery in older adults. Development of a more robust predictive model incorporating the KPS and TUG into the CARG model could be considered.

Prospective comparison between provider’s assessment and geriatric assessment among older adults with gastroesophageal cancer.

e24013 Background: Geriatric Assessment (GA) can help oncologists determine fitness of their older patients for cancer therapy. Our objective was to identify gaps that exist in the care of older adults with gastroesophageal cancer (GEC). Methods: Patients age 65 or older with any stage of GEC were consented and completed a self-administered GA. The patient’s provider completed a baseline assessment (PA) and abnormalities detected by both assessments were centrally reviewed and compared. Geriatric domains assessed include functional status, nutrition, comorbidities, psychological distress, cognition, social support, chemotherapy toxicity risk, and financial toxicity. Any abnormalities found within an evaluated domain were considered in the analysis. Providers reviewed patient GA alongside indicated interventions and identified those they would implement. We compared the proportions detected/not detected by PA vs GA using McNemar’s test for paired data, and we measured agreement using Kappa statistics. This is an interim report of an ongoing trial with total accrual goal of 100 older adults with GEC. Results: 33 patients were enrolled at the time of the interim analysis, majority were male (22, 67%), median age 74 (65-91), with stage III (9, 50%) disease treated with combination chemotherapy (12, 36%). Cancer site was distributed between gastric (45%), esophageal (36%), GEJ (18%). 90% of patients had ECOG status 0 or 1. GA detected 164 abnormalities in geriatric domains, mean 5 per patient, and PA detected 104 abnormalities, mean 3 per patient (see Table). Significant difference in abnormality identification between GA and PA were seen in domains of nutrition, chemotherapy toxicity risk, financial toxicity and psychological distress. 37% of patients had abnormal TUG score and those patients were more likely to have other geriatric abnormalities detected by GA (6.2 vs 4.4). Providers for 28 patients (85%) indicated they would make at least one change, with the majority being referral to social work. Conclusions: Among older adults with gastroesophageal cancer, GA identifies more abnormalities as compared to routine provider’s assessment in most cases leading to important clinical interventions.[Table: see text]

Modified CARG score using data from the electronic health record to predict chemotherapy toxicity in older adults.

12038 Background: Older adults starting chemotherapy are at greater risk of toxicity compared with younger patients. Additional tools are needed to aid in management decisions for this population. The Cancer and Aging Research Group (CARG) chemotherapy toxicity calculator is one such tool, which stratifies older adults into high, intermediate, or low risk for chemotherapy toxicity (Hurria, A., Mohile, S., Tew, W. P., &amp; et al. (2016). Validation of a prediction tool for chemotherapy toxicity in older adults with cancer. Journal of Clinical Oncology, 34(20), 2366–2371. https://doi.org/10.1200/jco.2015.65.4327). This tool relies on a face-to-face encounter to ask questions, e.g. “How is your hearing?” or “Can you take your own medicines?” in addition to lab values such as hemoglobin and creatinine clearance. We modified the CARG chemo toxicity calculator to include data points which could be pulled from the electronic health record (EHR) without the need for a face-to-face encounter to assess for an association with emergency department (ED) visits and hospital admissions. Methods: Retrospective data analysis was conducted using the EHR of patients over age 65 diagnosed with a solid tumor from 1/1/2019 to 12/31/2020 who started chemotherapy. A modified CARG score was calculated using age, cancer type, number of drugs, hemoglobin, creatinine clearance, and falls within the past 6 months. The remaining items needed to calculate the complete CARG score were excluded since they were not accessible in the EHR. We assessed ED visits leading to admission, ED visits leading to discharge, direct admissions, and the total of all 3 visit types for all patients. Results: A modified CARG score was calculated for 763 patients. Multiple models were evaluated and negative binomial distribution was found to be the best fitted for our data. For every one unit increase in our calculated score the number of ED visits which lead to hospital admission increased by 6% (p-value = 0.0156). Additionally, there was a 5% increase in combined ED visits, ED visits leading to admission, and direct admissions for every one unit increase in risk score (p-value = 0.0063). ED visits that did not lead to admission were found not to have an association with the risk score (p-value= 0.1263). (Table) Conclusions: A modified CARG score using data obtained from patients’ EHR had a statistically significant association with increased ER visits that resulted in hospital admission and with the total of ED visits leading to admission, ED visits leading to discharge, direct admissions. Using these outcomes as a surrogate for toxicity, we deduce that a simple tool could be used to predict chemotherapy toxicity in older adults. [Table: see text]

Prevalence and outcomes of frailty in older patients with cancer: A prospective study from geriatric oncology clinic.

e24011 Background: Frail older patients present with increased symptom burden, medical complexity and reduced tolerance to medical and surgical interventions. Data regarding the prevalence of frailty and its association with outcomes, such as overall survival, is limited from India. This study aimed to establish the prevalence of frailty and its association with overall survival (OS) in older patients with cancer. Methods: This was a prospective study conducted in geriatric oncology clinic of Tata memorial hospital (Mumbai India). Patients aged 60 years and above referred to the clinic were included. Frailty was identified using the Rockwoods Clinical frailty scale, and patients with a score of five or more were diagnosed as frail. Demographic details, type of cancer, stage and multi-domains geriatric assessment was done. Cancer and Ageing Research group online toxicity tool was used to assess the chemotherapy toxicity risk. A t-test or two-sample Wilcoxon rank-sum test was used to study the association between frailty status and non-categorical variables and the Pearson chi-squared test was used to measure the association between categorical variables. The Kaplan Meier survival estimation and the Cox proportional hazard model were used to perform the survival analysis. Results: Between June 2018 to January 2022, 909 patients were evaluated and 662 patients with clinical frailty score were included. The median age was 68 (60-86) years and 107 (16%) were above the age of 75 years. The most common malignancies were lung (39%), esophagus (21%) and head and neck (10%); 53% had metastatic disease. 192 (29%) were frail, and it prevalence increased with age. Frailty status was associated with poor OS (unadjusted HR: 2.512; 95% CI: 1.931-3.268). This association was significant even after adjusting for age, gender, BMI and stage of cancer (adjusted HR: 2.104; 95% CI: 1.598-2.770). Frailty was associated with comorbidities such as diabetes (32% vs 23%, p = 0.014), chronic obstructive pulmonary disease (13% vs 7%, p = 0.045) and cardiovascular disease (19% vs 12%, p = 0.017). Among the geriatric domains, frail patients had greater incidence of polypharmacy (52% vs 33%, p &lt; 0.01), slower gait speed (53% vs 12%, p &lt; 0.01), impaired cognition (25% vs 7%, p &lt; 0.01), poor nutritional status (51% vs 17%, p &lt; 0.001), depression (29% vs 8%, p &lt; 0.01) and anxiety (14% vs 5%, p &lt; 0.01). Conclusions: The prevalence of frailty among older cancer patients is high. It is associated with poor physical, cognitive and psychological resilience and is associated with poor overall survival. Our study supports the routine assessment of frailty in older patients with cancer to guide treatment decisions. Clinical trial information: CTRI/2020/04/024675.

Dose Modification of Etoposide plus Platinum in Elderly Patients with Extensive-Disease Small-Cell Lung Cancer

Background: Elderly patients with extensive-disease small-cell lung cancer (ED-SCLC) have a high risk of chemotherapy toxicity due to multiple comorbidities and poor performance status. Although dose modification is often used to avoid toxicity in elderly patients with ED-SCLC, there is little data on the effect of initial dose-reduced chemotherapy on survival outcomes. Methods and Patients: We retrospectively reviewed 100 elderly patients (≥70 years) with ED-SCLC who received first-line etoposide plus platinum chemotherapy between January 2006 and December 2020. Results: The median age was 74 years. Eighty-nine patients (89%) had a history of smoking, and 38 (38%) had chronic lung disease. Thirty-four patients (34%) received dose-reduced etoposide plus platinum in the first cycle. The dose-reduced group had significantly higher age, lower body mass index, and poor Eastern Cooperative Oncology Group Performance Score. There were no significant differences in survival outcomes between the dose-reduced and full-dose chemotherapy (median overall survival [OS], 4.9 vs. 6.5 months, p = 0.440; median progression-free survival [PFS], 3.7 vs. 4.6 months, p = 0.272). In multivariate analyses, DR in the first cycle (hazard ratio 0.519, 95% CI: 0.269–1.000, p = 0.050) was significantly associated with OS. Following a subgroup analysis of 59 patients who received minimum four cycles, no significant differences in survival outcomes between the two groups (median OS, 10.9 vs. 9.4 months, p = 0.817; median PFS, 6.3 vs. 6.5 months, p = 0.902) were noted. Conclusions: The dose-reduced chemotherapy with first-line etoposide plus platinum had non-inferior survival outcomes compared to the full-dose chemotherapy in elderly patients with ED-SCLC.

Prospective comparison of the value of CARG, G8, and VES-13 toxicity tools in predicting chemotherapy-related toxicity in older Turkish patients with cancer

BackgroundIn older patients with cancer, it is very important to choose the appropriate treatment because they are at high risk for chemotherapy toxicity. Our study investigated characteristics of Cancer and Aging Research Group (CARG), Geriatric 8 (G8), and Vulnerable Elders Survey (VES-13) screening tools for predicting chemotherapy-related toxicity (CRT) prospectively. Materials and methods208 patients aged ≥65 years old for whom chemotherapy was planned to treat non-haematological cancer between February 2021–September 2021 were included in the study. The CARG, G8, and VES-13 toxicity tools were completed by the oncologist through face-to-face interviews before starting the first chemotherapy treatment. CRTs during chemotherapy were evaluated according to the National Cancer Institute's Common Terminology Criteria for Adverse Events v4.03. Logistic regression models, the area under the receiver operating characteristic curve (ROC-AUC), and correlation analyses were used for comparing questionnaires. ResultsMedian age was 70.4 (range 65–86) years. Of the participants, 103 (49.5%) participants experienced grade 3–5 CRT (32.2% haematological, 28.4% non-haematological) during chemotherapy. ROC-AUC value of CARG was determined as 0.827 (95% CI [confidence interval]: 0.77–0.88, p < 0.001), it was determined as 0.744 (95% CI: 0.68–0.81, p < 0.001) for G8 and 0.726 (95% CI: 0.66–0.80, p < 0.001) for VES-13. In the univariate regression analysis, CARG (OR [odds ratio] = 13.57, 95% CI: 6.0–30.72, p < 0.001), G8 (OR = 3.19, 95% CI: 1.62–6.29, p = 0.001), and VES-13 (OR = 9.5, 95% CI: 5.01–17.89, p < 0.001) were found to be predictive for CRT. The multivariate analysis (included stage, Eastern Cooperative Oncology Group [ECOG] performance status, presence of comorbid disease, platinum-based treatment regimen, taxane-based treatment regimen, CARG, VES-13, G8) showed that CARG (OR = 12.08, 95% CI: 5.11–28.56, p < 0.001), VES-13 (OR = 10.06, 95% CI: 4.92–22.98, p < 0.001), and G8 (OR = 2.20, 95% CI: 1.04–4.69, p = 0.040) screening tools were strong predictors for CRT. The CARG and VES-13 questionnaires were predictive for reducing the initial treatment dose (p = 0.004, p = 0.004, respectively), interruption of treatment (p < 0.001, p < 0.001, respectively), discontinuing treatment (p = 0.002, p = 0.002, respectively), and unexpected hospitalisation (p = 0.012, p = 0.003, respectively). ConclusionsWe showed that all three CARG, G8, and VES-13 questionnaires are helpful tools in the decision-making process for ideal chemotherapy to predict severe CRT; however, CARG and VES-13 questionnaires appear more useful in daily oncology practice than the G8 questionnaire.

Implementing the cancer and aging research group (CARG) tool in the ambulatory oncology setting to drive informed treatment selection.

209 Background: Smilow Cancer Hospital is a NCI designated cancer center in Connecticut that has built a network of 15 community-based oncology (CBO) clinics. Older patients present with unique clinical challenges including multiple comorbidities, decreased functional status, and cognitive impairment. ASCO Geriatric Oncology guidelines recommend completing both a comprehensive geriatric assessment and a chemotherapy toxicity risk assessment on all oncology patients ≥65 years old for informed treatment selection. The CARG calculator is a simple, validated tool to assess chemotherapy toxicity risk in older patients with solid tumors. Despite ASCO guidelines, the existence of validated tools, and literature confirming improved patient outcomes, oncologists’ utilization of risk calculators is limited; therefore, we conducted a pilot CARG quality improvement initiative throughout our CBO network. Methods: 36 CBO physicians agreed to complete five CARG tools, document toxicity scores in the EMR, and complete a post-survey between March and June 2021. PDSA cycles included interventions of a hyperlink to the CARG tool incorporated in the EMR and creating a dot phrase built to simplify documentation. Education was provided on both the CARG and the survey. The survey captured perceived clinical value, time commitment, and barriers to implementation. Baseline data was collected during February 2021 and included geriatric patients receiving a new chemotherapy regimen for a solid tumor. Results: 180 consecutive new chemotherapy starts in geriatric patients were monitored. The CARG score utilization in new chemotherapy starts increased from 6.5% of new cases during the first month, to 26.4% in the third month. 82% of providers found the CARG score helpful in discussing chemotherapy risks with patients. In 32% of cases, the CARG score led to a decision to dose attenuate, and in 15% of cases, the CARG score led to a different treatment regimen. Most oncologists (65%) reported spending ≤5 minutes calculating toxicity, and 88% spent ≤10 minutes. 89% of oncologists reported the CARG score was worth the added time. Conclusions: This QI initiative demonstrates feasibility and increased use of the CARG geriatric chemotherapy toxicity tool in accordance with ASCO geriatric guideline-based care. Physician education and EMR workflow modification were utilized. In the CBO setting, oncologists found the CARG tool to be quick and helpful in discussing treatment risks with patients. Use of the CARG tool led to meaningful changes in treatment, including chemotherapy dose attenuation. Further study metrics such as palliative and supportive care referrals, ED visits, and hospitalizations will fuel sustainability.

Estimating the Risk of Chemotherapy Toxicity in Indian Geriatric Patient Population and Utility of Chemotherapy Risk Assessment Scale for High Age Patients (CRASH) Score.

Background Aging is a heterogeneous process, and elderly population is diverse in health status and functional reserve. The present study was undertaken to predict severe chemotherapy toxicity using the Chemotherapy Risk Assessment Scale for High-Age Patients’ (CRASH) score. Materials and Methods Elderly patients (age ≥65 years) with malignancy, who were planned to be treated with a new course of cytotoxic chemotherapy, were enrolled. The CRASH score was calculated, and patients were stratified into four categories, that is, low (0–3), intermediate (Int)-low (4–6), Int-high (7–9), and high (<9). Patients developing grade 3/4/5 nonhematologic (NH) or grade 4/5 hematologic (H) toxicity were taken as the development of severe toxicity. Results Of 100 enrolled patients, 64 (64%) were able to complete their prescribed treatment. Forty-four percent of patients (44 patients) of our study cohort experienced grade-4 H or grade 3/4 NH toxicity. The highest score in each category (heme/nonheme/CRASH) predicts nearly 100% toxicity risk. At a critical value of CRASH ≥ 6.5, the sensitivity is calculated as 100%, while specificity is 89.09%. The accuracy of prediction is 93.88%. The median time taken to develop toxicity was 39.5 days. Conclusion CRASH score utilizes clinical assessment and basic laboratory values. Yet, it accurately predicts severe chemotherapy toxicity above a critical value of 6.5. Based on the above study, the first 30 days are crucial as 45% of patients experienced toxicity in this time frame. With the help of these clinical predictive markers, the care of elderly will be optimized.

Prephase rituximab/prednisone therapy and aging-related, proinflammatory cytokine milieu in older, vulnerable patients with newly diagnosed diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) predominantly affects older adults with suboptimal therapeutic outcomes due to increased treatment-related mortality and toxicities in vulnerable patients, clinically defined by geriatric impairments such as functional limitation, multimorbidity, or cognitive deficits. In this prospective pilot study, we evaluated a rituximab/prednisone prephase treatment strategy in 33 older, vulnerable patients with newly diagnosed DLBCL, defined by either age ≥70 years or age 60-70 years with Karnofsky performance scale (KPS) <80. A single dose of rituximab 375 mg/m2 between 3-10 days and oral prednisone for at least 5 days prior to the first dose of chemoimmunotherapy was administered. All patients completed prephase treatment and all but one commenced anthracycline-based chemoimmunotherapy. Only one early cycle death occurred. Toxicity events, defined by either unplanned hospitalization, unplanned dose reduction/delay, or chemotherapy discontinuation, occurred in 22 patients (67%). Sixteen patients (48%) experienced grade 3 or higher non-hematologic toxicities and/or grade 4 or higher hematologic toxicities. With a median follow-up of 4.4 years, both 5-year progression-free survival and overall survival were at 81% (95% confidence interval: 69-96). Importantly, we found that phenotypic impairments in basic and instrumental activities of daily living, physical function, mobility, KPS, and Cancer and Aging Research Group chemotherapy toxicity risk score were significantly associated with senescence-associated, proinflammatory cytokine milieu which was readily reversed with prephase treatment, potentially explaining its clinical effectiveness. Prephase therapy with rituximab/prednisone should be considered for all older, vulnerable DLBCL patients prior to curative intent, anthracycline-based chemoimmunotherapy. This trial was registered as clinicaltrials gov. Identifier: NCT 89028394.

An exploratory study of body composition as a predictor of dose-limiting toxicity in metastatic pancreatic cancer treated with gemcitabine plus nab-paclitaxel

Body composition is increasingly being studied as a method of predicting chemotherapy toxicity. Our study aimed to evaluate associations of body composition with treatment toxicity in a group of pancreatic cancer patients treated with gemcitabine plus nab-paclitaxel. A retrospective review was performed for all patients who received first-line gemcitabine plus nab-paclitaxel for metastatic pancreatic cancer at a northern Alberta cancer institute (Canada) from 2014 to 2017. Total lean body mass (LBM) was derived from measurements of muscle surface area at L3 on baseline computed tomography (CT) scans. Optimal stratification, or minimal p-value analysis, was used to assess for a threshold of nab-paclitaxel dose per LBM (mg/kg) associated with a higher risk of dose-limiting toxicity (DLT). 152 patients were included in the study, of whom 62 (40.8%) experienced DLT. nab-Paclitaxel dose/LBM ranged from 0.98 to 8.76mg/kg. A threshold for nab-paclitaxel dose/LBM that optimally predicted risk of DLT was identified at 5.83mg/kg. Above this cut-off, 18/31 (58.1%) patients experienced DLT, compared to 44/121 (36.4%) patients below (p=0.028). Patients above this cut-off had a higher incidence of peripheral neuropathy compared to those below, though this was not statistically significant based on an adjusted p-value threshold (48.4 vs. 29.8% respectively, p=0.050). Body mass index, body surface area, and absolute initial doses of nab-paclitaxel or gemcitabine did not significantly impact likelihood of DLT. nab-Paclitaxel dose normalized to LBM, based on CT-derived measures of skeletal muscle, has potential to predict risk of chemotherapy toxicity. Chemotherapy dosing based on body composition, rather than conventional anthropometric measures, may be effective in reducing treatment toxicity.

Does oxaliplatin pharmacokinetics (PKs) explain associations between body composition and chemotherapy toxicity risk in older adults with gastrointestinal (GI) cancers?

3095 Background: Considerable inter-individual variability in oxaliplatin toxicity exists in older adults with GI cancers. Low lean body mass (LBM), commonly known as sarcopenia, influences toxicity and is not incorporated in standard body surface area-based dosing, which may affect oxaliplatin PK and tolerability, but has not been examined systematically. Methods: We examined oxaliplatin PK in 26 older adults (103 concentrations) with GI cancers (NCT03998202). Using the transverse section at L3, skeletal muscle area (SMA) and total adipose tissue (TAT) were quantified (Slice-O-Matic software) and LBM was calculated (LBM = 0.30 × SMA + 6.06). Noncompartmental methods (WinNonlin 7.0) were used for PK estimates and a one compartment population PK model (PopPK) was developed. Covariates included age, sex, LBM, TAT, weight, BMI, creatinine clearance, BSA, serum albumin, and body composition phenotypes (i.e. low LBM-high TAT, etc.). Results: Median age was 68yrs, 69% male, 88% white, and mostly colorectal (62%) and pancreatic (27%) cancers. There was wide variability in oxaliplatin volume of distribution (Vd: 12.5-259L), peak concentrations (Cmax: 404-3642ng/mL), and clearance (CL: 26.7-270L/hr). Participants with lower LBM had lower Vd (r = 0.51, p&lt; 0.01); those with higher TAT had higher Cmax (r = 0.53, p&lt; 0.01). Higher albumin was associated with lower Cmax (r = -0.49, p= 0.01) and higher CL (r = 0.47, p= 0.01). The phenotype of low LBM + high TAT had the lowest Vd (Relative Risk [RR] 0.32, p= 0.01), lowest CL (RR 0.39, p&lt; 0.01), and highest Cmax (RR 3.3, 95% CI 1.7-6.5, p&lt; 0.01). Eleven patients (44%) had grade 3-5 chemotoxicity. Vd (r = -0.46, p= 0.02) and Cmax (r = 0.44, p= 0.03) were associated with grade 3-5 chemotoxicity. The phenotype of low LBM + high TAT was associated with a 45% higher risk of grade 3-5 chemotoxicity (RR = 1.45, 95% CI 1.1-2.1, p= 0.04), while BSA was not (r = -0.04, p= 0.9). In the popPK model, body composition was associated with PK (TAT with Vd [p = 0.006] and CL [p &lt; 0.001]), as was albumin (Vd p = 0.004; CL p = 0.002), while BSA was not (Vd p = 0.08; CL p = 0.2). Compared to BSA, an additional 11-17% in oxaliplatin PK variability was explained by LBM (11%), TAT (14%), and albumin (17%). Conclusions: Relationships between body composition, oxaliplatin PK, and severe chemotoxicity suggest the need for novel dosing strategies that incorporate body composition to reduce chemotoxicity and improve outcomes. Clinical trial information: NCT03998202.

Accuracy of the CARG chemotherapy toxicity risk prediction tool in older Indian patients with cancer.

e24023 Background: Clinical judgement alone is inadequate in accurately predicting chemotherapy toxicity in older adult cancer patients. Hurria and colleagues developed and validated, the CARG score (range, 0–17) as a convenient and reliable tool for predicting chemotherapy toxicity in older cancer patients in America, however, its applicability in Indian patients is unknown. Methods: An observational retrospective and prospective study between 2018 and 2020 was conducted in the Department of Medical Oncology at Tata Memorial Hospital, Mumbai, India. The study was approved by the institutional ethics committee (IEC-III; Project No. 900596) and registered in the Clinical Trials Registry of India (CTRI/2020/04/024675). Written informed consent was obtained in the prospective part of the study. Patients aged ≥ 60 years and planned for systemic therapy were evaluated in the geriatric oncology clinic and their CARG score was calculated. Patients were stratified into low (0-4), intermediate (5-9) and high risk (10-17) based on the CARG scores. The CARG score was provided to the treating physicians, along with the results of the geriatric assessment. Chemotherapy-related toxicities were captured from the electronic medical record and graded as per the NCI CTCAE, version 4.0. Results: We assessed 130 patients, with a median age 69 years (IQR, 60 to 84); 72% patients were males. The common malignancies included gastrointestinal (52%) and lung (30%). Approximately 78% patients received polychemotherapy and 53% received full dose chemotherapy. Based on the CARG score, 28 (22%) patients belonged to low risk, 80 (61%) to intermediate risk and 22 (17%) to the high risk category. The AU-ROC of the CARG score in predicting grade 3-5 toxicities was 0.61 (95% CI, 0.51-0.71). The sensitivity and specificity of the CARG score in predicting grade 3-5 toxicities were 60.8% and 78.6%. Grade 3-5 toxicities occurred in 6/28 patients (21%) in the low risk group, compared to 62/102 patients (61%) in the intermediate /high risk group, p = 0.0002. There was also a significant difference in the time to development of grade 3-5 toxicities, which occurred at a median of 2.5 cycles (IQR, 1-3.8) in the intermediate /high risk group and at a median of 6 cycles (IQR, 3.5-8) in the low risk group, p = 0.0011. Conclusions: In older Indian patients with cancer, the CARG score reliably stratifies patients into low risk and intermediate/high risk categories, predicting both the occurrence and the time to occurrence of grade 3-5 toxicities from chemotherapy. The CARG score may aid the oncologist in estimating the risk-benefit ratio of chemotherapy. An important limitation was that we provided the CARG score to the treating oncologists prior to the start of chemotherapy, which may have resulted in alterations in the chemotherapy regimen and dose and may have impacted the CARG risk prediction model. Clinical trial information: CTRI/2020/04/024675.

The longitudinal relationship between immune cell profiles and frailty in patients with breast cancer receiving chemotherapy

BackgroundFrailty is associated with an increased risk of chemotherapy toxicity. Cellular markers of inflammation can help identify patients with frailty characteristics. However, the role of cellular markers of inflammation in identifying patients at risk of developing chemotherapy-induced frailty and their clinical utility are not fully understood.MethodsThis study was a secondary analysis of a large nationwide cohort study of women with stage I–IIIC breast cancer (n = 581, mean age 53.4; range 22–81). Measures were completed pre-chemotherapy (T1), post-chemotherapy (T2), and 6 months post-chemotherapy (T3). Frailty was assessed at all three time points using a modified Fried score consisting of four self-reported measures (weakness, exhaustion, physical activity, and walking speed; 0–4, 1 point for each). Immune cell counts as well as neutrophil to lymphocyte ratio (NLR) and lymphocyte to monocyte ratio (LMR) were obtained at T1 and T2 time points. Separate linear regressions were used to evaluate the associations of (1) cell counts at T1 with frailty at T1, T2, and T3 and (2) change in cell counts (T2–T1) with frailty at T2 and T3. We controlled for relevant covariates and frailty at the T1 time point.ResultsFrom T1 to T2, the mean frailty score increased (1.3 vs 2.0; p < 0.01) and returned to T1 levels by the T3 time point (1.3 vs 1.3; p = 0.85). At the T1 time point, there was a positive association between cellular markers of inflammation and frailty: WBC (β = 0.04; p < 0.05), neutrophils (β = 0.04; p < 0.05), and NLR (β = 0.04; p < 0.01). From T1 to T2, a greater increase in cellular markers of inflammation was associated with frailty at T2 (WBC: β = 0.02, p < 0.05; neutrophils: β = 0.03, p < 0.05; NLR: β = 0.03; p < 0.01). These associations remained significant after controlling for the receipt of growth factors with chemotherapy and the time between when laboratory data was provided and the start or end of chemotherapy.ConclusionsIn patients with breast cancer undergoing chemotherapy, cellular markers of inflammation are associated with frailty. Immune cell counts may help clinicians identify patients at risk of frailty during chemotherapy.Trial registrationClinicalTrials.gov, NCT01382082

Development and Validation of a Risk Tool for Predicting Severe Toxicity in Older Adults Receiving Chemotherapy for Early-Stage Breast Cancer.

Limited tools exist to predict the risk of chemotherapy toxicity in older adults with early-stage breast cancer. Patients of age ≥ 65 years with stage I-III breast cancer from 16 institutions treated with neoadjuvant or adjuvant chemotherapy were prospectively evaluated for geriatric and clinical features predictive of grade 3-5 chemotherapy toxicity. Logistic regression with best-subsets selection was used to identify and incorporate independent predictors of toxicity into a model with weighted variable scoring. Model performance was evaluated using area under the ROC curve (AUC) and goodness-of-fit statistics. The model was internally and externally validated. In 473 patients (283 in development and 190 in validation cohort), 46% developed grade 3-5 chemotherapy toxicities. Eight independent predictors were identified (each assigned weighted points): anthracycline use (1 point), stage II or III (3 points), planned treatment duration > 3 months (4 points), abnormal liver function (3 points), low hemoglobin (3 points), falls (4 points), limited walking (3 points), and lack of social support (3 points). We calculated risk scores for each patient and defined three risk groups: low (0-5 points), intermediate (6-11 points), or high (≥ 12 points). In the development cohort, the rates of grade 3-5 chemotherapy toxicity for these three groups were 19%, 54%, and 87%, respectively (P < .01). In the validation cohort, the corresponding toxicity rates were 27%, 45%, and 76%. The AUC was 0.75 (95% CI, 0.70 to 0.81) in the development cohort and 0.69 (95% CI, 0.62 to 0.77) in the validation cohort. Risk groups were also associated with hospitalizations and reduced dose intensity (P < .01). The Cancer and Aging Research Group-Breast Cancer (CARG-BC) score was developed and validated to predict grade 3-5 chemotherapy toxicity in older adults with early-stage breast cancer.

Perspectives on functional status in older adults with cancer: An interprofessional report from the International Society of Geriatric Oncology (SIOG) nursing and allied health interest group and young SIOG

Most adults with cancer are over 65 years of age, and this cohort is expected to grow exponentially. Older adults have an increased burden of comorbidities and risk of experiencing adverse events on anticancer treatments, including functional decline. Functional impairment is a predictor of increased risk of chemotherapy toxicity and shorter survival in this population. Healthcare professionals caring for older adults with cancer should be familiar with the concept of functional status and its implications because of the significant interplay between function, cancer, anticancer treatments, and patient-reported outcomes. In this narrative review, we provide an overview of functional status among older patients with cancer including predictors, screening, and assessment tools. We also discuss the impact of functional impairment on patient outcomes, and describe the role of individual members of an interprofessional team in addressing functional impairment in this population, including the use of a collaborative approach aiming to preserve function.