Impact of KRAS mutations and co-mutations on clinical outcomes in pancreatic ductal adenocarcinoma.

The relevance of KRAS mutation alleles to clinical outcome remains inconclusive in pancreatic adenocarcinoma (PDAC). We conducted a retrospective study of 803 patients with PDAC (42% with metastatic disease) at MD Anderson Cancer Center. Overall survival (OS) analysis demonstrated that KRAS mutation status and subtypes were prognostic (p < 0.001). Relative to patients with KRAS wildtype tumors (median OS 38 months), patients with KRASG12R had a similar OS (median 34 months), while patients with KRASQ61 and KRASG12D mutated tumors had shorter OS (median 20 months [HR: 1.9, 95% CI 1.2-3.0, p = 0.006] and 22 months [HR: 1.7, 95% CI 1.3-2.3, p < 0.001], respectively). There was enrichment of KRASG12D mutation in metastatic tumors (34% vs 24%, OR: 1.7, 95% CI 1.2-2.4, p = 0.001) and enrichment of KRASG12R in well and moderately differentiated tumors (14% vs 9%, OR: 1.7, 95% CI 1.05-2.99, p = 0.04). Similar findings were observed in the external validation cohort (PanCAN's Know Your Tumor® dataset, n = 408).

Impact of KRAS Mutations and Co-mutations on Clinical Outcomes in Pancreatic Ductal Adenocarcinoma.

The relevance of KRAS mutation alleles to clinical outcome remains inconclusive in pancreatic adenocarcinoma (PDAC). We conducted a retrospective study of 803 PDAC patients (42% with metastatic disease) at MD Anderson Cancer Center. Overall survival (OS) analysis demonstrated that KRAS mutation status and subtypes were prognostic (p<0.001). Relative to patients with KRAS wildtype tumors (median OS 38 months), patients with KRASG12R had a similar OS (median 34 months), while patients with KRASQ61 and KRASG12D mutated tumors had shorter OS (median 20 months [HR: 1.9, 95% CI 1.2-3.0, p=0.006] and 22 months [HR: 1.7, 95% CI 1.3-2.3, p<0.001], respectively). There was enrichment of KRASG12D mutation in metastatic tumors (34% vs 24%, OR: 1.7, 95% CI 1.2-2.4, p=0.001) and enrichment of KRASG12R in well and moderately differentiated tumors (14% vs 9%, OR: 1.7, 95% CI 1.05-2.99, p=0.04). Similar findings were observed in the external validation cohort (PanCAN's Know Your Tumor® dataset, n=408).

Achievement of personalized pain goal in cancer patients referred to a supportive care clinic at a comprehensive cancer center.

BACKGROUND: Cancer pain initiatives recommend using the personalized pain goal to tailor pain management. This study was conducted to examine the feasibility and stability of personalized pain goal, and how it compares to the clinical pain response criteria. METHODS: Records of 465 consecutive cancer patients seen in consultation at the Supportive Care Clinic were reviewed. Pain relief was assessed as clinical response (≥30% or ≥2 point pain reduction) and personalized pain goal response (pain ≤ personalized pain goal). RESULTS: One hundred fifty-two (34%), 95 (21%), and 163 (37%) patients presented with mild (1-4), moderate (5-6), and severe (7-10) pain, respectively. Median age (59 years), males (52%), and advanced cancer status (84%) did not differ by pain category. Median personalized pain goal at initial clinic consult was 3 (interquartile range, 2-3), was similar across pain groups, and remained unchanged (P = .57) at follow-up (median, 14 days). Clinical response was higher among patients with severe pain (60%) as compared with moderate (40%) and mild pain (33%, P < .001). Personalized pain goal response was higher among patients with mild pain (63%) as compared with moderate (44%) and severe pain (27%, P < .001). By using personalized pain goal response as the gold standard for pain relief, the sensitivity of clinical response was highest (98%) among patients with severe pain, but it had low specificity (54%). In patients with mild pain, clinical response was most specific for pain relief (98%), but had low sensitivity (52%). CONCLUSIONS: Personalized pain goal is a simple patient-reported outcome for pain goals. The majority of patients were capable of stating their desired level for pain relief. The median personalized pain goal was 3, and it was highly stable at follow-up assessment.

Factors associated with response to methylphenidate in advanced cancer patients.

BACKGROUND: There has been increasing interest in the use of methylphenidate for cancer-related fatigue (CRF) in patients with advanced cancer. However, there is limited literature on the specific patient characteristics associated with response to methylphenidate. Our objective of this study was to identify the specific patient characteristics associated with response to methylphenidate and to compare day 1 response with day 8 response. METHODS: We retrospectively reviewed the records of patients in two prospective controlled clinical trials that we had conducted who had received methylphenidate for cancer-related fatigue. Baseline patient characteristics, symptoms (as assessed by the Edmonton Symptom Assessment System [ESAS] and Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-F]), and response (change in fatigue) at the end of day 1 treatment were analyzed to determine their association with response to methylphenidate on day 8. RESULTS: A total of 82 patients with advanced cancer who received methylphenidate for CRF were included in our review. The median age was 55 years, 66% were female, 74% were white, and the most common cancer type was breast (37%). Fifty out of 82 patients (61%) responded to methylphenidate (≥ 7 points in FACIT-F). The intensity of baseline fatigue positively correlated with the response to methylphenidate (p < .001). Change in fatigue in response to methylphenidate was not associated with intensity of baseline depression, anxiety, drowsiness, or daily opioid dose. Better improvement of fatigue after treatment on day 1 was associated with more improvement with fatigue on day 8 as assessed by FACIT-F (p = .0004) and ESAS (p = .0001). Day 1 response as a predictor of day 8 response had a sensitivity of 0.84, a positive predictive value of 0.67, and specificity of 0.6. CONCLUSIONS: Response to methylphenidate is associated with higher baseline fatigue but not with higher baseline depression or sedation. Additionally, day 1 improvement is highly sensitive as a predictor of long-term improvement.

Association between a name change from palliative to supportive care and the timing of patient referrals at a comprehensive cancer center.

PURPOSE: Palliative care consultation services are now available in the majority of cancer centers, yet most referrals to palliative care occur late. We previously found that the term "palliative care" was perceived by oncology professionals as a barrier to early patient referral. We aimed to determine whether a service name change to supportive care was associated with earlier referrals. PATIENTS AND METHODS: Records of 4,701 consecutive patients with a first palliative care consultation before (January 2006 to August 2007) and after (January 2008 to August 2009) the name change were analyzed, including demographics and dates of first registration to hospital, advanced cancer diagnosis, palliative care consultation, and death. One-sample proportions tests, median tests, χ(2) tests, and log-rank tests were used to identify group differences. RESULTS: The median age was 59 years, 50% were male, and 90% had solid tumors. After the name change, we found: (a) a 41% greater number of palliative care consultations (1,950 versus 2,751 patients; p < .001), mainly as a result of a rise in inpatient referrals (733 versus 1,451 patients; p < .001), and (b) in the outpatient setting, a shorter duration from hospital registration to palliative care consultation (median, 9.2 months versus 13.2 months; hazard ratio [HR], 0.85; p < .001) and from advanced cancer diagnosis to palliative care consultation (5.2 months versus 6.9 months; HR, 0.82; p < .001), and a longer overall survival duration from palliative care consultation (median 6.2 months versus 4.7 months; HR, 1.21; p < .001). CONCLUSION: The name change to supportive care was associated with more inpatient referrals and earlier referrals in the outpatient setting. The outpatient setting facilitates earlier access to supportive/palliative care and should be established in more centers.

Impact of a palliative care consultation team on cancer-related symptoms in advanced cancer patients referred to an outpatient supportive care clinic.

CONTEXT: Patients with advanced cancer may develop severe physical and psychosocial symptoms. There are limited data on the impact of an outpatient palliative consultation (PC) team on cancer-related symptoms. OBJECTIVES: To study the impact of the PC on symptoms in patients with advanced cancer receiving outpatient palliative care. METHODS: Four hundred six consecutive patients referred to a supportive care outpatient center (OPC) from January 2006 to June 2007 with complete Edmonton Symptom Assessment Scale (0-10 scale) at the initial and follow-up visits were reviewed. Patient characteristics, change of symptoms at follow-up visit, and response rate were analyzed. Using logistic regression models, the predictors of improvement of pain and fatigue were assessed. RESULTS: Median age was 59 years; 53% were female. Median interval between visits was 15 days. Mean scores at baseline and follow-up visits were fatigue 6.8 and 5.3 (P<0.0001), pain 5.3 and 4.1 (P<0.0001), depression 3.2 and 2.5 (P<0.0001), anxiety 3.7 and 2.8 (P<0.0001), dyspnea 2.7 and 2.5 (P=0.05), sleep 5 and 4 (P<0.0001), and well-being 5.2 and 4.4 (P<0.0001). Dyspnea (odds ratio and P-value, 0.90, 0.03), nausea (0.92, 0.06), and depression (0.91, 0.04) were associated with improvement in fatigue; drowsiness (1.10, 0.04), and feeling of well-being (0.87, 0.02) were associated with improvement in pain. CONCLUSION: The initial consult by PC achieved significant symptom improvement in patients receiving treatment in the OPC. Further prospective studies are needed.

Single- vs. multiple-item instruments in the assessment of quality of life in patients with advanced cancer.

Although multidimensional instruments are usually used to measure quality of life in advanced cancer patients, recent research suggests that single-item assessments can provide a reliable measure. Using the Functional Assessment of Cancer Therapy-General (FACT-G) instrument as a gold standard, we assessed the performance of the Edmonton Symptom Assessment System "feeling of well-being" (ESAS WB) item. We reviewed the data from 213 patients enrolled in six clinical trials. We determined the association between baseline ESAS WB and FACT-G total and subscale domain scores (Physical Well-being [PWB], Social/Family Well-being [SWB], Emotional Well-being [EWB], and Functional Well-being [FWB]. We also calculated the association between baseline (T1) and second (T2) observations of ESAS WB and of FACT-G total score. In addition, we predicted the change in FACT-G predicted by the ESAS WB score using regression analysis. Mean age was 60 (SD 12) years and 48% were female. The Spearman correlation coefficient of ESAS WB and FACT-G was -0.48 (P<0.0001). Correlations with FACT-G subscale domains were also highly significant, except for the SWB domain (P=0.08). The Pearson correlation coefficient for T1-T2 in ESAS WB and FACT-G for 146 patients was -0.36 (P<0.0001). The change in ESAS WB corresponding to FACT-G published minimally important difference was -0.24 for 3, -1.55 for 5, and -2.87 for 7, respectively. These results suggest that the single-item measure ESAS WB best reflects the total score on the FACT-G and PWB, EWB, and FWB domains but not on the SWB domain.

Alcoholism screening in patients with advanced cancer: impact on symptom burden and opioid use.

PURPOSE: Alcoholism is a devastating disease that can cause patient and family suffering and is frequently underdiagnosed. Preliminary studies suggest that it is associated with increased symptom expression and opioid dose escalation. The CAGE questionnaire is a widely used tool for alcoholism screening. The purpose of this study was to determine the frequency and characteristics of patients who screen positive for alcoholism in a palliative care outpatient clinic (PCOC). METHODS: We reviewed 665 consecutive charts of patients referred to the PCOC and collected data regarding age, gender, and type of cancer. For the first 100 consecutive CAGE positive (CAGE+) and 100 consecutive CAGE negative (CAGE-) patients, time from advanced cancer diagnosis (AC) to PCOC was calculated, and symptoms (Edmonton Symptom Assessment Scale, ESAS) and Morphine Equivalent Daily Dose (MEDD) were collected. RESULTS: CAGE was available for 598 of 665 (90%) patients. Of 598 patients, 100 (17%) were CAGE+. CAGE+ patients were younger (58 versus 60 years, p < 0.05), predominantly male (68% versus 47%, p < 0.0001), and with head/neck malignancies (24% versus 9%, p < 0.05). CAGE+ patients were referred earlier (5 +/- 27 months after AC, p < 0.0001). At baseline, pain, sleep, dyspnea, well-being, and total symptom distress were significantly worse among CAGE+ patients. Both groups showed similar improvement in symptoms. CAGE+ patients were more frequently on opioids upon referral (47/100 versus 29/100, p < 0.05) and follow-up (27/65 versus 16/68, p < 0.05). At follow-up, opioid doses did not show significant changes. CONCLUSION: Seventeen percent of the patients were CAGE+. These patients were referred earlier to palliative care, had more symptom expression, and were more frequently on opioids. The palliative care team successfully improved symptom control in both groups without opioid dose escalation.

Interval between first palliative care consult and death in patients diagnosed with advanced cancer at a comprehensive cancer center.

PURPOSE: Most referrals to palliative care and hospice occur late in the trajectory of the disease although an earlier intervention could decrease patients' symptom distress. The purpose of this study was to determine the interval between first palliative care consult (PC1) and death (D) in patients diagnosed with advanced cancer (aCA) at our comprehensive cancer center and if such interval has increased over time. METHODS: The study group was 2868 consecutive patients who had their PC1 during a 30-month period. We reviewed the charts for information about demographics, cancer type, date of cancer (CA) diagnosis, aCA diagnosis, PC1, and D. aCA was defined as locally recurrent or metastatic. RESULTS: One thousand four hundred four patients (49%) were female, 1791 (62%) were less than 65 years old, 2563 (89%) had solid tumors, and 2004 (70%) were white. The median PC1-D, aCA-PC1, aCA-D, and CA-D intervals were 42, 147, 250, and 570 days, respectively. The median PC1-D interval was longer in patients with solid tumors (p < 0.0001), less than 65 years old (p = 0.002), and females (p = 0.004). PC1-D was not affected by ethnicity (p = 0.42). The median PC1-D interval in 5 consecutive half-years was 46, 56, 42, 41, and 34 days, respectively (p = 0.02). The number of PC1 in this period increased from 544 to 654 (20%). The ratio of PC involvement in the aCA-D period (PC1-D/aCA-D) decreased from 0.30 to 0.26 over the 5 half-year periods (p = 0.0004). CONCLUSIONS: The first palliative care consultation to death interval has decreased over time at our center. Education is needed among our referring physicians for earlier access to palliative care. Prospective studies are needed to establish the appropriate timing of the first palliative care consultation.