RECIST has subsequently been widely accepted as a standardized measure of tu-mor response, especially in clinical trials where the primary end points are objective response or time to progression [2]. Howev-er, with rapid technical innovations in imag-ing techniques, such as MDCT and PET/CT, over the past decade, the limitations of the original RECIST and the need for revision have become clear [2, 3].
In January 2009, a revised RECIST guide-line (version 1.1) was published by the RECIST Working Group, based in part on the investi-gations using the database consisting of more than 6,500 patients with more than 18,000 target lesions [2, 4–6]. Major imaging-relat-ed changes in RECIST 1.1 included a reduc-tion in the number of lesions to be assessed, from a maximum of 10 to a maximum of five and from five per organ to two per organ;
New Response Evaluation Criteria in Solid Tumors (RECIST) Guidelines for Advanced Non –Small Cell Lung Cancer: Comparison With Original RECIST and Impact on Assessment of Tumor Response to Targeted Therapy
Mizuki Nishino 1
David M. Jackman 2Hiroto Hatabu 3Beow Y. Yeap 4
Leigh-Anne Cioffredi 2Jeffrey T. Yap 1Pasi A. J?nne 2
Bruce E. Johnson 2
Annick D. Van den Abbeele 1
1
Department of Radiology, Dana-Farber Cancer Institute, 44 Binney St., Boston, MA 02116. Address correspon-dence to M. Nishino (Mizuki_Nishino@https://www.doczj.com/doc/2712564458.html,).2Department of Medical Oncology, Dana-Farber Cancer Institute and Brigham and Women’s Hospital, Boston, MA.3Department of Radiology, Brigham and Women’s Hospital, Boston, MA.
4Department of Medicine, Massachusetts General Hospital, Boston, MA.Ca rdiopulmona r y Imaging ? Or igina l Resea rch
WEB
This is a Web exclusive article.AJR 2010; 195:W221–W2280361–803X/10/1953–W221? American Roentgen Ray Society
O
bjective assessment of the change in tumor burden is important for evaluating the tumor response to anticancer drugs as a surrogate for
symptomatic response, and objective response has been shown to be closely correlated with prolonged survival with solid tumors. The Re-sponse Evaluation Criteria in Solid Tumors (RECIST) guideline was introduced in 2000 by an international working group to standard-ize and simplify tumor response criteria [1]. The key features of the original RECIST (ver-sion 1.0) included definitions of minimum CT size of measurable lesions, instructions on how many lesions to follow (up to 10, with a maximum of five per organ), and the use of unidimensional CT measures for overall evaluation of tumor burden [1, 2]. RECIST supplanted the bidimensional tumor size as-sessment that had been in common use.
Keywords: CT, lung cancer, PET/CT, Response Evaluation Criteria in Solid Tumors (RECIST), tumor measurement DOI:10.2214/AJR.09.3928
Received November 6, 2009; accepted after revision January 30, 2010.
The authors received support from Agfa HealthCare (2009–2010 RSNA Research Scholar Grant to
M. Nishino); the National Institutes of Health (grant 5R21CA11627-02 to H. Hatabu and grant 1RO-1CA114465-01 to B. Y. Yeap, P. A. J?nne, and
B. E. Johnson); the National Cancer Institute Specialized Program of Research Excellence in Lung Cancer (grant 2P50CA090578-06 to B. Y. Yeap, P. A. J?nne, and B. E. Johnson); Genentech, Inc.; and the Doris and William Krupp Research Fund in Thoracic Oncology.OBJECTIVE. The purpose of this article is to compare the recently published revised Response Evaluation Criteria in Solid Tumors (RECIST) guidelines (version 1.1) to the original guidelines (RECIST 1.0) for advanced non–small cell lung cancer (NSCLC) after erlotinib therapy and to evaluate the impact of the new CT tumor measurement guideline on response assessment.
MATERIALS AND METHODS. Forty-three chemotherapy-naive patients with ad-vanced NSCLC treated with erlotinib in a single-arm phase 2 multicenter open-label clini-cal trial were retrospectively studied. CT tumor measurement records using RECIST 1.0 that were generated as part of the prospective clinical trial were reviewed. A second set of CT tu-mor measurements was generated from the records to meet RECIST 1.1 guidelines. The num-ber of target lesions, best response, and time to progression were compared between RECIST 1.1 and RECIST 1.0.
RESULTS. The number of target lesions according to RECIST 1.1 decreased in 22 pa-tients (51%) and did not change in 21 patients (49%) compared with the number according to RECIST 1.0 (p < 0.0001, paired Student’s t test). Almost perfect agreement was observed be-tween best responses using RECIST 1.1 and RECIST 1.0 (weighted κ = 0.905). Two patients with stable disease according to RECIST 1.0 had progressive disease according to RECIST 1.1 criteria because of new lesions found on PET/CT. There was no significant difference in time to progression between RECIST 1.1 and RECIST 1.0 (p = 1.000, sign test).
CONCLUSION. RECIST 1.1 provided almost perfect agreement in response assess-ment after erlotinib therapy compared with RECIST 1.0. Assessment with PET/CT was a major factor that influenced the difference in best response assessment between RECIST 1.1 and RECIST 1.0.
Nishino et al.
assessment of lymph node size (lesions ≥ 15 mm in the short axis are considered measur-able and assessable as target lesions, and the short-axis measurement should be included in the sum of lesions in calculation of the tu-mor response); clarification of disease pro-gression (in addition to the previous defini-tion of progression in target disease of 20% increase in sum, a 5-mm absolute increase is now required); and inclusion of FDG PET assessment exclusively in the section on de-tection of new lesions [2] (Table 1).
It is anticipated that the new guideline im-proves feasibility and provides more accu-rate assessment of tumor response and time to progression while incorporating the cur-rent state-of-art imaging in the clinical on-cologic practice. However, it remains to be seen how RECIST 1.1 will affect the selec-tion and the CT measurement of the target le-sions, assessment of tumor response to ther-apy, and time to progression compared with RECIST 1.0.
Lung cancer is a leading cause of cancer death in the United States and worldwide, accounting for over 150,000 deaths per year in the United States [7]. Eighty-five percent of subjects have non–small cell lung can-cer (NSCLC), for which the 5-year surviv-al rate is only 15% [7]. Newer therapeutic agents have been clinically applied for lung cancer, including erlotinib, an inhibitor of the tyrosine kinase domain of the epidermal growth factor receptor [8–10]. Erlotinib can be associated with dramatic clinical response in patients with epidermal growth factor re-
ceptor mutations. However, patients with an
initial response to erlotinib eventually have
a relapse due to development of acquired re-
sistance [11–13]. With the emerging preclini-
cal understanding of the mechanisms of erlo-
tinib resistance, new therapies targeting these
mechanisms are being developed. Therefore,
the accurate CT tumor measurement and re-
sponse assessment in advanced NSCLC treat-
ed with targeted therapy are critically im-
portant to determine the timing to adjust the
therapeutic regimen for further prolongation
of survival.
The purpose of this study is to compare CT
tumor measurement and tumor response as-
sessment based on RECIST 1.1 versus RECIST
1.0 in a phase 2 clinical trial of patients with ad-
vanced NSCLC treated with erlotinib.
Materials and Methods
Patients and Treatment
The original clinical trial was already per-
formed with 80 eligible patients [14]. The study
was approved by the Dana-Farber/Harvard Can-
cer Center institutional review board. Of 80 pa-
tients, complete CT tumor measurement records
were available for 43 patients. Therefore, the study
population of the current study consisted of 43 pa-
tients (22 men and 21 women; mean age, 77 years;
range, 70–91 years) with histologically confirmed
stage IIIB/IV NSCLC that had not been treated
with chemotherapy. Patients enrolled in this phase
2 multicenter open-label study were treated with
150 mg of erlotinib by mouth each day as part of
first-line therapy between March 2003 and May
2005 [14]. Thirty-nine patients were treated at the
Dana-Farber Cancer Institute, and four patients
were treated at the Massachusetts General Hospi-
tal. All patients gave written informed consent. Pa-
tients were treated without interruption until dis-
ease progression, severe or intolerable toxicity, or
withdrawal of consent. Compliance was checked
after each 28-day cycle with a treatment diary.
CT Examinations
CT scans of the chest were obtained at baseline
and at every two cycles (8 weeks) of therapy to
determine response to erlotinib or progression of
disease. Each clinical trial site used their standard
clinical chest CT protocol with iodinated IV con-
trast agent unless medically contraindicated. The
protocol at the Dana-Farber Cancer Institute was
as follows: a 4-MDCT scanner (Volume Zoom,
Siemens Healthcare) was used. Patients were
scanned in the supine position from the cranial
to caudal direction from the clavicles to the adre-
nal glands at end-inspiration. One hundred micro-
liters of iopromide (300 mg I/mL; Ultra v ist 300,
Bayer HealthCare Pharmaceuticals) was injected
IV with an automated injector (Stellant, Medrad)
at a rate of 2–3 mL/s, with a scan delay of 30 sec-
onds. Axial images (5 or 7 mm thickness) were
reconstructed using standard and lung algorithms
and were transferred to the PACS.
CT Tumor Measurement and Assessment
of Tumor Response to Therapy
CT tumor measurement was prospectively per-
formed by attending radiologists at Dana-Farber
Cancer Institute and was recorded at the baseline
and at every follow-up CT examination according
to the original RECIST 1.0 criteria as a part of the
ongoing phase 2 clinical trial [14]. The longest di-
ameter of each target lesion was manually mea-
sured by radiologists on an axial CT image plane
using calipers of a measurement tool on PACS.
The CT tumor measurement record included the
number of the treatment cycle, the date of assess-
ment, the clinical site where imaging was per-
formed, the method of imaging, the target lesion
description and CT size measurement, the sum of
the longest tumor diameters of target lesions, de-
scriptions of nontarget lesions, the presence or ab-
sence of new lesions, the overall response for each
imaging study, and the best response and time to
progression for each patient.
The results of the RECIST 1.0 CT measurements
for the completed clinical trial were retrospectively
reviewed by a board-certified thoracic radiologist
who was blinded to the patients’ outcome, to gen-
erate a second set of CT tumor measurements that
meet the RECIST 1.1 guideline. Briefly, the tar-
TABLE 1: Summary of Major Changes in Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 Compared With RECIST 1.0 RECIST Guideline RECIST 1.1RECIST 1.0
No. of target lesions Up to 2 per organ; up to 5 in total Up to 5 per organ; up to 10 in total Assessment of lymph nodes Short-axis measurements should be
used and recorded; ≥ 15 mm, target
lesions; ≥ 10 mm but < 15 mm,
nontarget lesions; < 10 mm,
nonpathological
No clear guideline provided
Clarification of disease progression 20% increase in the sum of target
lesions and 5-mm absolute
increase are required
20% increase in the sum of
target lesions (no minimum
absolute size increase is
required)
FDG PET scan Included only in the detection of new
lesions a
Not included
a New lesions on the basis of FDG PET can be identified according to the following algorithm [2]: a negative FDG PET at baseline with a positive FDG PET at follow-up is a sign of progressive disease based on a new lesion. For no FDG PET at baseline and a positive FDG PET at follow-up, if the positive FDG PET at follow-up corresponds to a new site of disease confirmed by CT, this is progressive disease. If the positive FDG PET at follow-up is not confirmed as a new site of disease on CT, additional follow-up CT scans are needed to determine whether there is truly progression occurring at that site. If the positive FDG PET at follow-up corresponds to a preexisting site of disease on CT that is not progressing on the basis of the anatomic images, this is not progressive disease.
Revised RECIST Guidelines for Lung Cancer
get lesions recorded in the original measurements were reassessed if they met the criteria of RECIST 1.1: lymph nodes less than 15 mm in the short axis were excluded from target lesions; when the num-ber of target lesions exceeded the limits according to RECIST 1.1 (up to five in total and up to two per organ), smaller lesions were eliminated from tar-get lesions; short-axis measurements were used for lymph nodes instead of long-axis measurements; and the PET/CT clinical reports were also reviewed for the patients who underwent PET/CT during the treatment to determine whether any new lesion was detected on PET/CT meeting the RECIST 1.1 criteria for progression. The number of RECIST 1.1 target lesions and the sums of tumor diameters at baseline and follow-up was calculated and re-corded. The percentage change in the sum of tu-mor diameters of target lesions was calculated and recorded at every two cycles of therapy. Tumor re-sponse to therapy was reassessed using the revised RECIST 1.1 for each CT measurement, and best re-sponse for each patient was assigned.
Time to progression and survival were calcu-lated from the date of enrollment to the date of progression, using RECIST 1.1 and RECIST 1.0, or to the time of death, respectively. Time to pro-gression was censored (i.e., losses from the sam-ple before the observation of the final outcome were taken into account) if an end point was not reached by the time of last follow-up, or if a pa-tient was lost to follow-up, or if it was not possible to determine the date of progression according to RECIST 1.1. Time to progression was estimated using the Kaplan-Meier method [15].
To assess interobserver variability, a new set of CT tumor measurements was obtained on the baseline CT scans of 39 patients treated at the Da-na-Farber Cancer Institute using RECIST 1.0 and RECIST 1.1 by a board-certified thoracic radiolo-gist. Of 43 patients, four were treated at an outside
institution, and their CT scans were not available
for this component of the study. The CT measure-
ment was performed using a measurement tool on
PACS workstation (Centricity, GE Healthcare).
The sum of the longest diameters of the target le-
sions measured by this observer using RECIST
1.0 and RECIST 1.1 were compared with the CT
measurements obtained during the clinical trial
using RECIST 1.0 and RECIST 1.1, respectively.
The CT measurement performed during the clini-
cal trial (measurement 1) and that performed by
the observer in the present study (measurement
2) were compared using Pearson’s correlation and
linear regression. Agreement in the two CT mea-
surements was shown visually using Bland-Alt-
man plots with 95% limits of agreement [16, 17].
Statistical Analysis
A paired Student’s t test was used to assess the
statistical significance of changes in the number
of target lesions and the sum of lesion diameters
at baseline between RECIST 1.1 and RECIST
1.0. The baseline CT measurements by RECIST
1.1 versus RECIST 1.0 as well as the percentage
changes in follow-up CT measurements relative to
baseline were compared using Pearson’s correla-
tion and linear regression.
The level of agreement between best responses
by RECIST 1.1 versus RECIST 1.0 was assessed us-
ing a weighted kappa analysis based on the absolute
difference of equally spaced scores. Agreement be-
tween the two assessments was categorized as poor
(weighted κ < 0), slight (weighted κ = 0–0.20), fair
(weighted κ = 0.21–0.40), moderate (weighted κ =
0.41–0.60), substantial (weighted κ= 0.61–0.80),
and almost perfect (weighted κ > 0.80) [18].
Time to progression according to RECIST 1.1
versus RECIST 1.0 was compared using a sign
test. All p values are based on a two-sided hypoth-
esis. A p value of less than 0.05 was considered to
be significant.
Results
The number of target lesions using RECIST
1.1 was significantly lower than that using
RECIST 1.0 (p < 0.0001, paired Student’s t
test), with a decrease in the lesion number in
22 patients (51%) and no change in the re-
maining 21 patients (49%) (Fig. 1). The num-
ber of target lesions according to RECIST 1.0
ranged from one to nine (mean, 2.7; median,
2; mode, 2), whereas the number of target le-
sions according to RECIST 1.1 ranged from
zero to five (mean, 1.8; median, 2; mode, 1).
The number of target lesions according to
RECIST 1.1 was decreased by one in 15 pa-
tients, by two in two patients, by three in two
patients, and by four in three patients, with
a mean decrease of 0.86. The number of the
target lesions was decreased as a result of the
new definition of measurability of malignant
lymph nodes at the baseline (a lymph node
must be 15 mm in the short axis to be consid-
ered pathologically enlarged and measurable
[2]), for 18 patients, and as a result of the re-
duction of the number of lesions required to
assess tumor burden (from a maximum of 10
to a maximum of five total, and from five to
two per organ, maximum), for four patients.
There were three patients who had no target
lesions when RECIST 1.1 was used. In these
patients, all the target lesions according to
RECIST 1.0 were lymph nodes smaller than
1.5 cm in the short axis and did not meet the
RECIST 1.1 criteria for a target lesion.
Comparison of the sum of tumor diam-
eters of target lesions on baseline CT mea-
surements by RECIST 1.1 and by RECIST
1.0 is shown in Figure 2A. A high correlation
was noted between the baseline CT measure-
ments by RECIST 1.1 and RECIST 1.0 (r =
0.936 and r2 = 0.876, Pearson’s correlation).
The baseline CT measurement using RECIST
1.1 was significantly smaller than that us-
ing RECIST 1.0, with a mean difference of
?1.6 cm and a regression slope of 0.73 (p =
0.0001, paired Student’s t test). The distribu-
tion of the differences between baseline CT
measurements by RECIST 1.0 and by RECIST
1.1 is shown in Figure 2B.
The percentage changes between RECIST
1.1 and RECIST 1.0 in the sum of tumor diam-
eters of target lesions showed a high correlation
(r = 0.986 and r2 = 0.972 at cycle 2 [n = 28]; r =
0.998 and r2 = 0.996 at cycle 4 [n = 7]; r = 0.657
and r2 = 0.432 at cycle 6 [n = 5]; r = 0.949 and
Fig. 1—Number of target lesions according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 versus that according to RECIST 1.0. Number of target lesions calculated using RECIST 1.1 was significantly lower than that calculated using RECIST 1.0 (p < 0.0001, paired Student’s t test).
Nishino et al.
r2 = 0.901 at cycle 8 [n = 4]; r = not applicable and r2 = not applicable at cycle 10, [n = 1]; and r = 0.979 and r2 = 0.959 at cycles 2–10 [n = 45], Pearson’s correlation) (Figs. 3 and 4). One pa-tient showed discrepant response assessment based on the percentage change in the sum of tumor diameters of target lesions according to RECIST 1.1 and RECIST 1.0 after the first two cycles of therapy (stable disease according to RECIST 1.1 and progressive disease according to RECIST 1.0; circle in Figure 3, asterisk in Figure 4). However, coincidently the patient also had a new lesion on CT performed at two cycles of therapy. Therefore, the overall re-sponse assessment of this patient at two cycles of therapy was progressive disease by both RECIST 1.1 and RECIST 1.0, resulting in the
same best response and time to progression by
RECIST 1.1 and by RECIST 1.0.
Of 43 patients, the best response according
to RECIST 1.1 was the same as the best re-
sponse according to RECIST 1.0 in 40 patients
(93%) and was different in three patients (7%).
Almost perfect agreement was observed be-
tween the best response according to RECIST 1.1
versus the best response according to RECIST
1.0 (weighted κ = 0.905) (Table 2). Among
three patients with differences in best response
according to RECIST 1.1 and RECIST 1.0,
two patients had stable disease based on
RECIST 1.0 but had progressive disease ac-
cording to RECIST 1.1 because of new lesions
noted on PET/CT. The other patient had pro-
gressive disease using RECIST 1.0 but was as-
sessed as stable disease according to RECIST
1.1 because of a new lesion by RECIST 1.0 that
was a lymph node measuring less than 10 mm
in the short axis, which does not meet the new
criteria of pathologic lymph node by RECIST
1.1. This patient was removed from the clin-
ical trial and the erlotinib therapy when pro-
gressive disease was determined on the basis
of RECIST 1.0, whereas the patient could have
continued the erlotinib therapy if RECIST 1.1
were used for assessment.
Of 43 patients, only six (14%) underwent
PET/CT during the course of the treatment.
Of these six patients, four had no findings on
PET/CT that influenced the assessment of re-
sponse therapy; however, two (33%) of the six
patients had new lesions on PET/CT, which
changed the best response from stable disease
to progressive disease. In the actual trial uti-
lizing RECIST 1.0, which does not include
new lesions on PET/CT as a criterion for dis-
ease progression, these two patients were not
considered to meet the criteria of progression
at the time of PET/CT and continued with the
trial. These two patients could have come off
the clinical trial sooner if RECIST 1.1 criteria
including PET/CT were used.
Fig. 2—Comparison of diameters of target lesions by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and 1.0.
A, Comparison of sum of longest diameters of target lesions on baseline CT measurements by RECIST 1.1 and RECIST 1.0 showed high correlation between two CT measurements (r = 0.936 and r2 = 0.8758, Pearson’s correlation).
B, Decrease in sum of longest diameters of target lesions on baseline CT measurements by RECIST 1.1 (B1.1) compared with baseline CT measurement RECIST 1.0 (B1.0) (p = 0.0001, paired Student’s t test).
Fig. 3—Percentage changes in sum of long diameter CT measurements by
Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 versus RECIST 1.0
at every two cycles of therapy. High correlation in percentage changes and
high concordance of response assessments were observed between CT
measurements by RECIST 1.1 and by RECIST 1.0. (r = 0.986 and r2 = 0.972 at cycle
2 [n = 28]; r = 0.998 and r2 = 0.996 at cycle 4 [n = 7]; r = 0.657 and r2 = 0.432 at cycle
6 [n = 5]; r = 0.949 and r2 = 0.901 at cycle 8 [n = 4]; r = not applicable and r2 = not
applicable at cycle 10 [n = 1]; and r = 0.979 and r2 = 0.959 at cycles 2–10 [n = 45],
Pearson’s correlation). PD = progressive disease, PR = partial response, SD =
stable disease.
Revised RECIST Guidelines for Lung Cancer
Time to progression did not show any sig-nificant difference (p = 1.000, sign test) be-tween RECIST 1.1 and RECIST 1.0 (Fig. 5). Time to progression between RECIST 1.1 and RECIST 1.0 did not differ in 40 patients (93%). Time to progression according to RECIST 1.1 was shorter than that according to RECIST 1.0 in two patients whose best re-sponse changed from stable disease according to RECIST 1.0 to progressive disease accord-ing to RECIST 1.1 (54 days according to RECIST 1.1 vs 108 days according to RECIST 1.0; and 51 days according to RECIST 1.1 vs 92 days according to RECIST 1.0). In one pa-tient whose best response changed from pro-gressive disease by RECIST 1.0 to stable dis-ease by RECIST 1.1, time to progression according to RECIST 1.1 was longer than that according to RECIST 1.0. For this patient, it was not possible to obtain the exact days of time to progression by RECIST 1.1 because the patient was removed from the protocol and the erlotinib therapy was discontinued at
the time of documented progression by RECIST 1.0 (54 days) in the actual clinical trial.A high correlation was noted between the CT measurement performed during the clinical trial (measurement 1) and that per-formed by the observer in the present study (measurement 2) for both RECIST 1.0 (r 2 = 0.9740, Pearson’s correlation) and RECIST 1.1 (r 2 = 0.9846, Pearson’s correlation) (Figs. 6A and 6B). Figures 6C and 6D show the Bland-Altman plots with the mean percent-age of relative difference and the limits of agreement. For the two CT measurements using RECIST 1.0, the mean difference was ?0.2% (95% limits of agreement, ?30.8%, 30.4%) (Fig. 6C). For the two measurements using RECIST 1.1, the mean difference was 3.4% (95% limits of agreement, ?18.6%, 25.4%) (Fig. 6D).
Discussion
The RECIST 1.1 criteria provided almost perfect agreement in the assessment of tu-mor response to therapy compared with the RECIST 1.0 criteria, with a decreased num-ber of target lesions in patients with NSCLC treated with targeted therapy. To our knowl-edge, this is the first report that evaluated the impact of RECIST 1.1 on CT tumor mea-surement and the response assessment since the new guideline has been published [2].The most common reason for the decrease in the number of target lesions using RECIST 1.1 was the new definition of measurability of malignant lymph nodes at the baseline (a lymph node must be at least 15 mm in the short axis to be considered pathologically enlarged and measurable as a target lesion [2]), which affected 18 patients. The new definition is intended to eliminate the inclu-sion of lymph nodes less than 15 mm in the short axis as target lesions [6]. Another rea-son for the decreased number of target le-sions was the reduction in the number of le-sions required to assess tumor burden (from
10075
50
25
P r o g r e s s i o n -F r e e P r o b a b i l i t y (%)
Time to Progression (d)
0150
120
90
60
30
RECIST 1.1RECIST 1.0
Fig. 4—Percentage changes in sum of longest diameter CT measurements by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and RECIST 1.0 after first two cycles of therapy. Response assessments of target
lesions at first two cycles of therapy by RECIST 1.1 and RECIST 1.0 were concordant in 27 (96%) of 28 patients and discordant in one patient (4%; asterisk ). PD = progressive disease, PR = partial response, and SD = stable disease.
Fig. 5—Time to
progression by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 versus RECIST 1.0. Difference in time to progression was not significant (p = 1.000, sign test).
TABLE 2: Best Response Assessment by Response Evaluation Criteria in
Solid Tumors (RECIST) 1.1 Versus RECIST 1.0
Best Response by RECIST 1.0Best Response by RECIST 1.1
Progressive Disease
Stable Disease
Nonevaluable
Progressive disease 1710Stable disease 2170Nonevaluable
6
Note—Data are number of patients. Weighted κ = 0.905.
Nishino et al.
a maximum of 10 to a maximum of five, and from five to two per organ), which influenced four patients [2]. Three of these four patients had three lesions in the lung according to RECIST 1.0. The smallest of the three le-sions at the baseline was excluded from the target lesions. The other patient had wide-spread disease in the chest, upper abdomen, and ribs, with a total of nine target lesions according to RECIST 1.0. The largest five le-sions by the longest diameter were chosen in keeping with the limit of two lesions per or-gan. Three patients (7%) had no target le-sions according to RECIST 1.1, because all the target lesions according to RECIST 1.0 were lymph nodes smaller than 1.5 cm in the short axis, which does not meet the RECIST 1.1 criteria for a target lesion. Hence, these three patients would be nonassessable patients
and would likely be excluded from participa-
tion in a prospective trial using RECIST 1.1.
The result indicates that RECIST 1.1 influenc-
es the eligibility of the patients for clinical trials,
which requires measurable lesion by RECIST at
baseline for enrollment.
The baseline RECIST CT measurement
was decreased in 25 patients (58%) when
RECIST 1.1 was used. The mean difference
in the baseline CT measurement of summed
lesion diameters was 1.6 cm, and 19 (76%)
of the 25 patients with decreases in baseline
CT measurement by RECIST 1.1 had reduc-
tions of less than 3 cm. The decrease in the
baseline CT size measurement was due to a
decrease in the number of target lesions in
22 patients. For three patients, the baseline
CT measurement by RECIST 1.1 was de-
creased because of the inclusion of the short-
axis measurement for the lymph node, rather
than the long axis, without a decrease in the
number of target lesions. The decrease in the
baseline CT measurement for these three pa-
tients was less than 1 cm. RECIST 1.1 pro-
vided concordant response assessment of
target lesions with RECIST 1.0 at each mea-
surement on CT scans at every two cycles of
therapy except for one (2.2%) of 45 patients.
New lesions noted on PET/CT changed
the best response for two patients from stable
disease according to RECIST 1.0 to progres-
sive disease according to RECIST 1.1. The
results suggest that the inclusion of PET/CT
in the assessment of new lesions may have a
significant influence on response assessment
Fig. 6—Comparison of sum of longest diameters of target lesions on baseline CT measurements performed in clinical trial (measurement 1) and by observer in present study (measurement 2).
A and B, High correlation was noted between two measurements for both Response Evaluation Criteria in Solid Tumors (RECIST) 1.0 (A) and RECIST 1.1 (B) (r2 = 0.9740 and r2 = 0.9846, respectively; Pearson’s correlation).
C and D, Bland-Altman plots of two sets of baseline CT measurements for RECIST 1.0 (C) and RECIST 1.1 (D) are shown. Interobserver variability is shown as function of mean of two measurements. Dotted lines indicate upper and lower 95% limits of agreement. Dashed lines indicate mean relative difference.
Revised RECIST Guidelines for Lung Cancer
by RECIST 1.1. In the current study, only six patients underwent PET/CT because PET/ CT was not a part of the clinical trial pro-tocol and was performed as a part of clin-ical care only if it was clinically indicated and requested by the referring physician. A study with a larger patient cohort with peri-odic PET/CT assessment is needed to further evaluate its impact.
Time to progression was different between RECIST 1.1 and 1.0 for only three patients (shortened for two and prolonged for one). In the cohort of 43 elderly patients with advanced NSCLC used in the present study, no patient showed complete or partial response. In a dif-ferent clinical subset with dramatic initial re-sponse to erlotinib and subsequent slow growth of the tumor, as seen in women who are nonsmokers or former smokers, RECIST 1.1 with new criteria of progression (i.e., a 5-mm absolute increase is now required for progressive disease) may have more influence in the assessment of time to progression.
In the assessment of interobserver vari-ability using two sets of CT measurements, the 95% limits of agreement were approxi-mately within plus or minus 30% for both RECIST 1.0 and RECIST 1.1. The results are similar to the recently published interobserv-er variability data of NSCLC tumor measure-ments by Zhao et al. [17], indicating that the CT tumor measurements are reproducible within the partial response category (?30%); however, this finding raises a concern about placing patients in the progression disease category (+20%) too easily [18]. Of note, the present study showed that the 95% lim-its of agreement were better in the measure-ments using RECIST 1.1 (?18.6%, 25.4%) than in the measurements using RECIST 1.0 (?30.8%, 30.4%). The result suggests that the use of RECIST 1.1 may improve the re-producibility of CT tumor measurements and therefore may contribute to the adequate re-sponse assessment after therapy by reflecting the true tumor size changes, rather than the changes resulting from measurement vari-ability. These findings require further inves-tigation and validation with a larger cohort and a larger number of radiologists.
The limitations of the present study in-clude a retrospective design and a relatively small number of patients. However, the CT tumor measurement records using RECIST 1.0 that we used in this study were prospec-tively performed during the clinical trial. We used these records to create a second set of CT tumor measurements meet RECIST 1.1 rather than reselecting and remeasuring the
lesions. We used this approach to avoid dif-
ferences of two RECIST measurements de-
rived from inherent inconsistency and lack
of reproducibility of CT tumor measure-
ments [19]. In the present study, our main
focus was the differences in CT measure-
ments resulting from changes in the RECIST
1.1 criteria. A study with independently per-
formed RECIST 1.1 and RECIST 1.0 mea-
surements in a larger study cohort is needed
to further address the impact of RECIST 1.1
in the actual clinical trial and patient man-
agement. Although it is important to consid-
er differences in survival using RECIST 1.1,
this previously performed clinical trial used
RECIST 1.0 for decision making, including
when to stop the targeted therapy. Therefore,
it is not possible to adequately compare sur-
vival for RECIST 1.1 and RECIST 1.0 using
the data from this cohort. One would ideal-
ly need to compare survival in a prospective
trial randomized by the two RECIST criteria
(version 1.1 vs 1.0) for treatment decisions.
Additional potential limitations include the
exclusion of nearly half the original trial pa-
tients from this study because original mea-
surements were not available and biases of
lesion selection that might have occurred in
the conversion to RECIST 1.1.
Assessment of tumor burden by CT tumor
measurement using RECIST is an important
feature of the clinical evaluation of cancer
therapy and determines the end points of on-
cologic clinical trials. Radiologists, who in-
terpret the oncology CT scans on daily basis,
play a major role in CT tumor measurement
by selecting, measuring, and reporting the
lesions. It is important for radiologists to be
aware of the changes in the new RECIST 1.1
guideline and its impact on CT tumor mea-
surements as shown in the present study. First,
a reduction in the maximum number of target
lesions results in a decrease in the number of
target lesions; thus, the time and efforts of
radiologists are reduced when RECIST 1.1
is used. Second, the new definition of mea-
surability of malignant lymph nodes contrib-
utes to reducing the number of target lesions
and influences the eligibility for clinical tri-
als in patients who have lymph nodes only
as measurable lesions. Third, the inclusion of
PET/CT in the detection of new lesions has a
major effect on altering the best response as-
sessment and time to progression.
In conclusion, RECIST 1.1 provided al-
most perfect agreement in the assessment
of tumor response to therapy compared with
RECIST 1.0, with decreased numbers of tar-
get lesions. Assessment with PET/CT was a
major factor that influenced the difference in
best response assessment between RECIST
1.1 and RECIST 1.0.
References
1. Therasse P, Arbuck SG, Eisenhauer EA, et al.
New guidelines to evaluate the response to treat-
ment in solid tumors (RECIST guidelines). J Natl
Cancer Inst 2000; 92:205–216
2. Eisenhauer EA, Therasse P, Bogaerts J, et al. New
response evaluation criteria in solid tumors: re-
vised RECIST guideline (version 1.1). Eur J Can-
cer 2009; 45:228–247
3. Suzuki C, Jacobsson H, Hatschek T, et al. Radio-
logic measurements of tumor response to treat-
ment: practical approaches and limitations. Ra-
dioGraphics 2008; 28:329–344
4. Bogaerts J, Ford R, Sargent D, et al. Individual
patient data analysis to assess modifications to the
RECIST criteria. Eur J Cancer2009; 45:248–
260
5. Moskowitz CS, Jia X, Schwartz LH, G?nen M. A
simulation study to evaluate the impact of the
number of lesions measured on response assess-
ment. Eur J Cancer 2009; 45:300–310
6. Schwartz LH, Bogaerts J, Ford R, et al. Evaluation
of lymph nodes with RECIST 1.1. Eur J Cancer
2009; 45:261–267
7. Jemal A, Siegel R, Ward E, et al. Cancer statistics,
2008. CA Cancer J Clin 2008; 58:71–96
8. Lynch TJ, Bell DW, Sordella R, et al. Activating
mutations in the epidermal growth factor receptor
underlying responsiveness of non-small-cell lung
cancer to gefitinib. N Engl J Med 2004; 350:2129–
2139
9. Paez JG, Janne PA, Lee JC, et al. EGFR mutations
in lung cancer: correlation with clinical response
to gefitinib therapy. Science 2004; 304:1497–1500
10. Pao W, Miller V, Zakowski M, et al. EGF receptor
gene mutations are common in lung cancers from
“never smokers” and are associated with sensitiv-
ity of tumors to gefitinib and erlotinib. Proc Natl
Acad Sci USA 2004; 101:13,306–13,311
11. Pao W, Miller VA, Politi KA, et al. Acquired re-
sistance of lung adenocarcinomas to gefitinib or
erlotinib is associated with a second mutation in
the EGFR kinase domain. PLoS Med 2005; 2:e73
12. Engelman JA, Zejnullahu K, Mitsudomi T, et al.
MET amplification leads to gefitinib resistance in
lung cancer by activating ERBB3 signaling. Sci-
ence 2007; 316:1039–1043
13. Kobayashi S, Boggon TJ, Dayaram T, et al. EGFR
mutation and resistance of non-small-cell lung can-
cer to gefitinib. N Engl J Med 2005; 352:786–792
14. Jackman DM, Yeap BY, Lindeman NI, et al. Phase
II clinical trial of chemotherapy-naive patients >
Nishino et al.
or = 70 years of age treated with erlotinib for ad-vanced non-small-cell lung cancer. J Clin Oncol 2007; 25:760–766
15. Kaplan EL, Meier P. Nonparametric estimation
from incomplete observations. J Am Stat Assoc 1958; 53:457–481
16. Bland JM, Altman DG. Statistical methods for as-
sessing agreement between two methods of clini-
cal measurement. Lancet 1986; 1:307–310
17. Zhao B, James LP, Moskowitz CS, et al. Evaluat-
ing variability in tumor measurements from
same-day repeat CT scans of patients with non-
small cell lung cancer. Radiology 2009; 252:263–
272
18. Kundel HL, Polansky M. Measurement of observ-
er agreement. Radiology 2003; 228:303–308
19. Erasmus JJ, Gladish GW, Broemeling L, et al. In-
terobserver and intraobserver variability in mea-
surement of non-small-cell carcinoma lung le-
sions: implications for assessment of tumor
response. J Clin Oncol 2003; 21:2574–2582
QBE (Query By Example) Criteria cri = session.createCriteria(Student.class); cri.add(Example.create(s)); //s是一个Student对象 list cri.list(); 实质：创建一个模版，比如我有一个表serial有一个giftortoy字段，我设置serial.setgifttoy("2"), 则这个表中的所有的giftortoy为2的数据都会出来 2: QBC (Query By Criteria) 主要有Criteria,Criterion,Oder,Restrictions类组成 session = this.getSession(); Criteria cri = session.createCriteria(JdItemSerialnumber.class); Criterion cron = Restrictions.like("customer",name); cri.add(cron); list = cri.list(); ============================== 比较运算符 HQL运算符QBC运算符含义 = Restrictions.eq() 等于 <> Restrictions.not(Exprission.eq()) 不等于 > Restrictions.gt() 大于 >= Restrictions.ge() 大于等于 < Restrictions.lt() 小于 <= Restrictions.le() 小于等于 is null Restrictions.isnull() 等于空值 is not null Restrictions.isNotNull() 非空值 like Restrictions.like() 字符串模式匹配 and Restrictions.and() 逻辑与 and Restrictions.conjunction() 逻辑与 or Restrictions.or() 逻辑或 or Restrictions.disjunction() 逻辑或 not Restrictions.not() 逻辑非 in(列表) Restrictions.in() 等于列表中的某一个值 ont in(列表) Restrictions.not(Restrictions.in())不等于列表中任意一个值 between x and y Restrictions.between() 闭区间xy中的任意值 not between x and y Restrictions.not(Restrictions..between()) 小于值X或者大于值y 3: HQL String hql = "select https://www.doczj.com/doc/2712564458.html, ,avg(s.age) from Student s group by https://www.doczj.com/doc/2712564458.html,"; Query query = session.createQuery(hql); list = query.list(); .... 4: 本地SQL查询 session = sessionFactory.openSession(); tran = session.beginTransaction();
Professional Studies Presentation Evaluation Criteria The numbers in the top of the boxes are points in a continuum. For example, you can assign 20 points for Organization. As long as you do not give more points than suggested in the leftmost box, the score will range between 0 and 100 when you add up the numbers. Organization (20%) 20 Consistently clear, concise, well organized. Points were easy to follow because of the organization. Transitions between sections smooth and coordinated. 15Usually clear, concise, well organized. Most of the presentation was easy to follow. Transitions between sections usually coordinated. 10Not always clear or concise. Organization was adequate, but weak. Occasionally wandered and was sometimes difficult to follow. Transitions between sections weak. 5Often unclear and disorganized, rambled too much. The presentation was confusing and difficult to follow. Transitions between sections awkward. Topic Knowledge (20%) 20Displayed an excellent grasp of the material. Demonstrated excellent mastery of content, application and implications. Excellent research depth. 15Displayed a general grasp of the material. Demonstrated good mastery of content, application and implications. Good research depth. 10Displayed some grasp of the material. Demonstrated adequate mastery of content, application and implications. Research not very deep. 5Displayed a poor grasp of the material. Demonstrated a superficial handling of content, application and implications. Little depth of research. Creativity (10%) 10Very creative and original. Imaginative design and use of materials. Novel handouts, visual aids, or methods. 8 Exhibited some originality and creativity. 5 Routine treatment, minimal thought given to originality or creativity. 3Lacked creativity. Very ordinary and mundane. Visual Aids (15%) 15Simple, clear, easy to interpret, easy to read. Well coordinated with content, well designed, used very effectively. Excellent example of how to prepare and use good visual aids 11Usually clear, easy to interpret, easy to read. Generally well coordinated with content, design was okay, generally used effectively. Demonstrated some understanding of how to use visual aids. 8 Marginally acceptable, too complex, crowded, difficult to read or interpret. Adequate coordination with content. Used only adequately. Showed little understanding of how to prepare and use visual aids. 4Poor quality visual aids (or none), hard to read, technically inaccurate, poorly constructed. Poor coordination with content. Used poorly. The presenter did not seem to know how to prepare or use visual aids effectively. Summary (15%) 15Clear, concise, major points emphasized, clear recommendations, strong conclusion or call for action. 11Referred to main points, recommendations weak or missing, weak conclusion or call for action. 8Vague mention of major points, no recommendations, weak conclusion, weak or no call for action. 4No summary, no recommendations, no conclusions, no call for action. Stage Presence (20%) 20 Excellent stage presence. Confident, used notes well, at ease, excellent gestures, good audience attention, good eye contact. 15Good stage presence. Fairly confident, used notes fairly well, good gestures, acceptable audience attention and eye contact. 10 Adequate stage presence. Read parts, fumbled with notes, several distracting mannerisms, minimal gestures, minimal eye contact, too many um=s. 5Poor stage presence. Unprepared, awkward, shuffled papers, poor eye contact, lots of um=s, turned from audience to read overheads, shuffled feet, fidgeted. Poor gestures. TOTAL POINTS COMMENTS:
Design Criteria Building optimization must be followed by design criteria; these design criteria are given by the corresponding code. With the aim to determine the optimization criteria I personally have chosen the IBC 2013 Code with the corresponding related codes, such as ACI 318 and ASCE-7, concrete and load codes. Firstly we should determine the basic requirements for a high-rise building with shear wall structure and deep foundation as a foundation system, being this kind of building the objective of the study in situ. ?Building use and occupancy: (CHAPTER 3)Residential group R-2, residential occupancies containing sleeping units or more than two dwelling units where the occupants are primarily permanent in nature, including: Apartment houses, Boarding houses (non-transient), Convents, Dormitories, Fraternities and sororities, Hotels (non-transient), I Live/work units, Monasteries, Motels (non-transient), Vacation timeshare properties. ?Requirements based on occupancy:(CHAPTER 4) 1. For buildings not greater than 420 feet (128 m) in building height, the fire-resistance rating of the building elements in Type IA construction shall be permitted to be reduced to the minimum fire-resistance ratings for the building elements in Type IB. 2. In other than Group F-1, M and S-1 occupancies, the fire-resistance rating of the building elements in Type IB construction shall be permitted to be reduced to the fire-resistance ratings in Type IIA. 3. Bond strength:
criteria范文 我抄袭作业的原因是因为我想早点写完作业早点玩，谁都想玩，但是假如为了玩就抄 作业的话太不值了，现在玩只能玩一会，假如学习不好，以后找不着工作，没钱吃饭，还 谈的上玩吗我抄袭作业抱有一种作业是做给老师看的这种想法，其实根本不是，我们不 做作业，老师就不用批改作业，反而更轻松。所以，作业是为自己做的，我这么想辜负了 老师的一片好心，所以，我向老师表现出深深地歉意! One point is clear that different issues have different objective criteria. For example, criteria of price talking will include factors of cost, market situation, depreciation, price competition and other necessary factors. In other negotiations, exper ts’ opinions, international conventions and norms and legal documents will all serve as objective criteria. 为解决本人衣服无人洗，饭菜无人做，花钱无节制，生活无压力的现状，本人新引进 一招商项目，将于2020年02月20(26)日17时30分举行盛大的庆典活动，请亲朋好友准时参加! In the Sino—US negotiation on China’s accession into WTO, the two parties disputed over China’s developing country status. US took the position that China should be treated as a developed country. To back US stance, American negotiators cited China’s growing exports and large foreign reserve holdings. They a rgued that in developing countries China’s sophisticated technology in launching and retrieving satellites had no parallel. One American negotiator even compared the situation in China with that in India and some African countries. He said when he opened the door of a family in a poorest area randomly chosen by the Chinese government and asked the people if they had their breakfast, he was told they did, and he went on asking if lunch and supper were guaranteed, the answer was yes. However he had a very different story in some African countries and even in some areas in India. People there had little food for breakfast, not mention lunch and supper. The two countries insisted on their own standards and it was hard to bridge the discrepancy. Here the focus is which criterion to apply to for resolving the dispute. In fact there is a ready criterion provided by the World Bank, which is measured by per capita GNP. According to the World Bank’s standard, countries whose per capita GNP below $785 (1996) are the poorest countries. China’s per capita GNP in 1997 was $750, which is among the poorest countries. 甲方聘用乙方的月薪为_____元(含养老、医疗、住房公积金)。试用期满后，并经考 核合格，可根据平等协商的原则，签订正式劳动合同。
复合查询主要是处理，具有关联关系的两个实体怎样进行关联查询，比如User 实体对象与Addres实体对象具有一对多的关联关系，我们可以如下构造 符合查询： Criteria criteria=session.createCriteria(User.class); Criteria addcriteria=criteria.createCriteria(“addresses”);(1) addcriteria.add(Express.like(“address”,”%tianjin%”)); List list=criteria.list(); for(int i=0;i User user=(User)list.get(i); System.out.println(user.getName()+”\n”); Set addresses=user.getAddresses(); Iterator it=addresses.iterator(); while(it.hasNext(){ Address address=(Address)it.next(); Syste m.out.println(address.getAddress()+”\n”); } } 当执行到了（1）处时，表明要针对User对象的addresses属性添加新的查询条件，因此当执行criteria.list()时，Hibernate会生成类似如下的SQL语句： Select * from user inner join address on user.id=address.id where address.address like …%shanghai%?; 正如我们所见，我们可以通过向Criteria中添加保存关联对象的集合属性（addresses属性保存与User对象相关联的Address对象），来构造复合查询，在数据库一端是通过内连接查询来实现。 Hibernate QBC查询 QBC查询：
Criteria的使用总结 1、目前只遇到用于单表查询（多表查询期待中。。。） public Integer getqueryTamArchivesCount(String content, String fileNumber, String fileType, Date beginDate,Date endDate){ DetachedCriteria criteria = DetachedCriteria .forClass(TamArch.class); if (content != null && content.trim().length() > 0) { //模糊匹配 criteria.add(Restrictions.like("subject", "%" + content + "%")); } if (fileNumber != null && fileNumber.trim().length() > 0) { //相等 criteria.add(Restrictions.eq("archivesNo", fileNumber)); } if ("1".equals(fileType)) { //或者 criteria.add(Restrictions.or(Restrictions.eq("archivesStatus", "1"), Restrictions.eq("archivesStatus", "2"))); }else if("2".equals(fileType)){ criteria.add(Restrictions.eq("archivesStatus", "99")); } if(beginDate!=null&&endDate!=null){ //两者之间 criteria.add(Restrictions.between("issueDate",beginDate,endDate)); } //按日期降序排列 criteria.addOrder(Order.desc("inputDate")); return archDao.getRowCount(criteria) ; } 注意： ①对于日期有点bug，如果查询的日期为空，则查询不到数据。貌似日期为必填。 ②对于Restrictions.or：只能处理2种的情况 ③ //处理或情况（archivesStatus为2、3、99） criteria.add(Restrictions.in("archivesStatus", new Object[]{"2","3","99"}));
Criteria的几种查询方法使用 QBC常用限定方法 Restrictions.eq --> equal,等于. Restrictions.allEq --> 参数为Map对象,使用key/value进行多个等于的比对,相当于多个Restrictions.eq的效果 Restrictions.gt --> great-than > 大于 Restrictions.ge --> great-equal >= 大于等于 Restrictions.lt --> less-than, < 小于 Restrictions.le --> less-equal <= 小于等于 Restrictions.between --> 对应SQL的between子句 Restrictions.like --> 对应SQL的LIKE子句 Restrictions.in --> 对应SQL的in子句 Restrictions.and --> and 关系 Restrictions.or --> or 关系 Restrictions.isNull --> 判断属性是否为空,为空则返回true Restrictions.isNotNull --> 与isNull相反 Restrictions.sqlRestriction --> SQL限定的查询 Order.asc --> 根据传入的字段进行升序排序 Order.desc --> 根据传入的字段进行降序排序 MacthMode.EXACT :字符串精确匹配。相当于like …value? MathMode.ANYWHERE:字符串在中间匹配.相当于like …%value%? MathMode.START:字符串在最前端匹配位置.相当于:like …value%? MatchMode.END:字符串在最后端匹配.相当于:like …%value? 1.查询年龄在20-30之间的所有学生对象。 List list = session.createCriteria(Student.class) .add(Restrictions.between(“amout”,new BigDecimal(1),new BigDec imal(10)).list(); 2.查询S tudent名字开头有t的所有Student: List list = sesison.createCriteria(Student.class) .add(Restrictions.like(“name”,”t%”)).list(); 3.或者使用另一种查询Student名字开头有t的所有Student: List list = sesison.createCriteria(Student.class)
本文是对深入浅出Hibernate学习做的学习笔记，是个人在对深入浅出Hibernate学习中的一点认识和看法，下边是具体的内容。 本文是对深入浅出Hibernate学习做的学习笔记，是个人在对深入浅出Hibernate学习中的一点认识和看法，下边是具体的内容。 Criteria Query通过面向对象的设计，将数据查询条件封装为一个对象。简单来说，Criteria Query可以看作是传统SQL的对象化表示，如： 1.Criteria criteria=session.createCriteria(TUser.class); 2.criteria.add(Expression.eq("name","Erica")); 3.criteria.add(Expression.eq("sex",new Integer(1)); 这里的criteria实例本质上是对SQL“select * from t_user where name='Erica' and sex=1”的封装。Hibernate在运行期会根据Criteria中指定的查询条件生成相应的SQL语句。 Criteria查询表达式：Criteria本身只是一个容器，具体的查询条件要通过Criteria.add方法添加到Criteria实例中。 方法描述：Expression.eq 对应SQL “field=value”表达式 如：Expression.eq("name","Erica") 4.Expression.allEq 参数为一个Map对象，其中包含了多个属性-值对应关系。相当于多个 Expression.eq关系的叠加 5.Expression.gt 对应SQL“field>value”表达式 6.Expression.ge 对应SQL“field>=v alue”表达式 7.Expression.lt 对应SQL“field 最近在项目中使用Spring 和Hibernate 进行开发，有感于Criteria 比较好用，在查询方法设计上可以灵活的根据Criteria 的特点来方便地进行查询条件的组装。现在对Hibernate的Criteria 的用法进行总结： Hibernate 设计了CriteriaSpecification 作为Criteria 的父接口，下面提供了Criteria和DetachedCriteria 。 Criteria 和DetachedCriteria 的主要区别在于创建的形式不一样，Criteria 是在线的，所以它是由Hibernate Session 进行创建的；而DetachedCriteria 是离线的，创建时无需 Session，DetachedCriteria 提供了 2 个静态方法forClass(Class) 或forEntityName(Name) 进行DetachedCriteria 实例的创建。Spring 的框架提供了getHibernateTemplate ().findByCriteria(detachedCriteria) 方法可以很方便地根据DetachedCriteria 来返回查询结 果。 Criteria 和DetachedCriteria 均可使用Criterion 和Projection 设置查询条件。可以设 置FetchMode( 联合查询抓取的模式) ，设置排序方式。对于Criteria 还可以设置FlushModel （冲刷Session 的方式）和LockMode （数据库锁模式）。 下面对Criterion 和Projection 进行详细说明。 Criterion 是Criteria 的查询条件。Criteria 提供了add(Criterion criterion) 方法来 添加查询条件。 hibernate:Hibernate中Criteria的完整使用方法 疯狂代码 https://www.doczj.com/doc/2712564458.html,/ ?:http:/https://www.doczj.com/doc/2712564458.html,/Java/Article58225.html 最近在项目中使用 Spring 和 Hibernate 进行开发有感于 Criteria 比较好用在查询思路方法设计上可以灵活根据 Criteria 特点来方便地进行查询条件组装现在对 HibernateCriteria 使用方法进行整理总结: Hibernate 设计了 CriteriaSpecication 作为 Criteria 父接口下面提供了 Criteria和DetachedCriteria Criteria 和 DetachedCriteria 主要区别在于创建形式不样 Criteria 是在线所以它是由 Hibernate Session 进行创建；而 DetachedCriteria 是离线创建时无需SessionDetachedCriteria 提供了 2 个静态思路方法forClass(Class) 或 forEntityName(Name) 进行DetachedCriteria 例子创建 Spring 框架提供了getHibernateTemplate.findByCriteria(detachedCriteria) 思路方法可以很方便地根据DetachedCriteria 来返回查询结果 Criteria 和 DetachedCriteria 均可使用 Criterion 和 Projection 设置查询条件可以设置 FetchMode( 联合查询抓取模式 ) 设置排序方式对于 Criteria 还可以设置 FlushModel(冲刷 Session 方式)和 LockMode (数据库锁模式) 下面对 Criterion 和 Projection 进行详细介绍说明 Criterion 是 Criteria 查询条件Criteria 提供了 add(Criterion criterion) 思路方法来添加查询条件 Criterion 接口主要实现包括: Example 、 Junction 和 SimpleExpression 而 Junction 实际使用是它两个子类 conjunction 和 disjunction 分别是使用 AND 和 OR 操作符进行来联结查询条件集合 Criterion 例子可以通过 Restrictions 工具类来创建Restrictions 提供了大量静态思路方法如 eq (等于)、ge (大于等于)、 between 等来思路方法创建 Criterion 查询条件 (SimpleExpression 例子)除此的外Restrictions 还提供了思路方法来创建 conjunction 和 disjunction 例子通过往该例子 add(Criteria) 思路方法来增加查询条件形成个查询条件集合 至于 Example 创建有所区别 Example 本身提供了个静态思路方法 create(Object entity) 即根据个对象(实际使用中般是映射到数据库对象)来创建然后可以设置些过滤条件: Example exampleUser =Example.create(u) .ignoreCase // 忽略大小写 CriteriaType _or 的使用 生成的语句： select * from (select this_.ID as ID13_0_, this_.USER_NAME as USER2_13_0_, this_.USER_ID as USER3_13_0_, this_.ORG_NAME as ORG4_13_0_, this_.ORG_ID as ORG5_13_0_, this_.DEPT_NAME as DEPT6_13_0_, this_.DEPT_ID as DEPT7_13_0_, this_.USER_TITLE as USER8_13_0_, this_.APPRAISER_NAME as APPRAISER9_13_0_, this_.APPRAISER_ID as APPRAISER10_13_0_, this_.APPRAISER_TITLE as APPRAISER11_13_0_, this_.APPRAISER_MIND as APPRAISER12_13_0_, this_.REVIEW_DATE as REVIEW13_13_0_, this_.REVIEW_STATUS as REVIEW14_13_0_, this_.YEAR as YEAR13_0_, this_.BEGIN_DATE as BEGIN16_13_0_, this_.END_DATE as END17_13_0_, this_.CREATE_DATE as CREATE18_13_0_, this_.SIGN_DATE as SIGN19_13_0_, this_.SIGN_STATUS as SIGN20_13_0_, this_.POSITION_DESC as POSITION21_13_0_, this_.SCORE as SCORE13_0_, this_.CONTRACT_TYPE as CONTRACT23_13_0_, this_.DEL_FLAG as DEL24_13_0_ from PERF_PA_APRL_CONTRACT this_ where ((this_.ID in (select this0__.ID from PERF_PA_APRL_CONTRACT this0__ where this0__.USER_ID = ?) or this_.ID in (select this0__.ID from PERF_PA_APRL_CONTRACT this0__ where this0__.APPRAISER_ID = ?)) and this_.DEL_FLAG = ?)) where rownum <= ? Criteria的一些语句范例（方法） 一、Criteria的一些基本查询 Criteria有一个方法add(“限定条件”)，这个方法可以添加限定条件，好得到自己应该要的查询结果；例如：有两个实体类，student和teacher已经有一个Criteria的关于Student 类的实例Criteria crit = session.createCriteria(Student.class)； 1）在一个班级中要查询姓“王”的学生都有谁，就可以这样:List list = crit.add(Restrictions.like(“name”,”王%”)).list(); 2）查询年龄在17-20之间的学生：List list = crit.add(Restrictions.between(“age”,new Integer(17),new Integer(20))).list(); 3）查询没有手机号码的学生：List list = crit.add(Restrictions.isNull(tel)).list(); 4）查询90后的学生：List list = crit.add(Restrictions.ge(new Date(1990-01-01)).list(); 5）查询考试分数在前十名的学生（可用于分页查询）：List list = crit.addOrder(Order.desc(“grades”)).setFirstResult(0).setMaxResult(10).list(); 6）查询学生小明的个人信息：crit.add(Restriction.eq(“name”,”小明”)).list().iterator().next(); 7）查询小明的化学教师的信息：crit.add(Restricrions.eq(“name”,”小明”)).createCriteria(“teacher_id”).add(Restrictions.equ(“subject”,”化 学”)).list().iterator().next(); 8）以上都是先创建session根据session得到Criteria的实体对象（即在线查询），下面来看看离线查询，离线查询用的是DetachedCriteria类，DetachedCriteria类使你 在一个session范围之外创建一个查询，并且可以使用任意的Session来执行它。 下面写还按照上面的条件，写一个例子吧： DetachedCriteria query = DetachedCriteria.forClass(Student.class) .add( Property.forName("name").eq("小明") ); Session session = Configuration().configure().buildSessionFactory().openSession; Transaction txn = session.beginTransaction(); List results = query.getExecutableCriteria(session).setMaxResults(100).list(); https://www.doczj.com/doc/2712564458.html,mit(); session.close(); 二、常用的一些基本的限定方法 Restrictions.eq --> equal,等于. Restrictions.allEq -->参数为Map对象,使用key/value进行多个等于的比对,相当于多个Restrictions.eq的效果 Restrictions.gt --> great-than >大于 Restrictions.ge --> great-equal >= 大于等于 Restrictions.lt --> less-than, <小于 Restrictions.le --> less-equal <= 小于等于 Restrictions.between -->对应SQL的between子句 Restrictions.like -->对应SQL的LIKE子句 Restrictions.in -->对应SQL的in子句 Restrictions.and --> and 关系Hibernate中Criteria的完整用法
Criteria用法详解
CriteriaType【_or、子查询】的使用
criteria的一些示例语句或方法
相关主题
文本预览